Well here's how I see things going:

Intel and AMD ditch their assembly architectures for Scratch, because drag and drop is very popular lately.

The Boolean is renamed to the biggot by SJW leaders for only supporting binary views.

You must first ask consent to add an item to a linked list, because forcing two items together promotes rape culture.

Apple removes the "h" and "7" keys on all laptop models and gives no reason for their actions.

Linus Torvalds grows an extra middle finger, and it still isn't enough.

Nintendo makes Mario gay and Luigi black to be more inclusive.

LG makes a curved monitor that curves away from you rather than towards you. People buy it in confusion.

Everyone makes the same ad revenue on YouTube, and it is rebranded to OurTube. Luckily, they were able to keep the color scheme.

People finally realize that machine learning is just math, and stop using it everywhere. (Just kidding lol)

AMD and Gucci merge. Nobody understands why.

Here's a list of unpopular stuff which I agree with:

1) I love Java more than any other programming language.

2) I love sleeping more than working.

3) I'm not a night owl. I thrive the most during daylight.

4) I don't like or need coffee. Tea is fine.

5) Webdev is a huge clusterfuck which I secretly wish that could just die already.

6) Cybersecurity is a meme and actually not that interesting. Same passes for Cloud, Machine Learning and Big Data.

7) Although I'm a huge fan of it Linux is too unstable and non-idiot proof to ever become mainstream on the desktop.

8) Windows is actually a pretty solid OS.

9) The real reason I don't use macos is because I'm a poorfag that can't afford an overpriced laptop.

10) I don't like math and I hate that people push math shit into random interview questions for dev jobs which have nothing to do with math.

Post yours.

Where do I even start?

Personal projects?
So many. Shouldn't count.

Unpaid game dev intern?
Unpaid game dev volunteer?
Both worthwhile, if stressful. Shouldn't count either.

Freelancing where clients refused to pay?
That's happened a few times. One of them paid me in product instead of cash (WonderSoil, a company that [apparently still] makes and sells some expanding super potting soil thing). The product turned out to be defective and killed all of the plants I used it on. I'd have preferred getting stiffed instead. Their "factory" (small, almost tiny) was quite cool. The owner was a bitch. Probably still is.

Companies that have screwed me out of pay?
So many. I still curse their names at least once a month. I've been screwed out of about $13k now, maybe more. I've lost track.

I have two stories in particular that really piss me off.

The first: I was working at a large robotics company, and mostly enjoyed my job, though the drive was awful. The pay wasn't high either, but I still enjoyed the work. Schedule was nice, too: 28 hours (four 7-hour days) per week. Regardless, I got a job offer for double my salary, same schedule, and the drive was 11 minutes instead of 40. I took it. My new boss ended up tricking me into being a contractor -- refused to give me a W2, no contracts, etc. Later, he also increased my hours to 40 with no pay increase. He also took forever to pay (weeks to months), and eventually refused to pay me to my face, in front of my cowokers. Asshole still owes me about $5k. Should owe me the the difference in taxes, too (w2 vs 1099) since he lied about it and forced me into it when it was too late to back out.

I talked to the BBB, the labor board, legal council, the IRS (because he was actively evading taxes), the fire inspector (because he installed doors taht locked if the power went out, installed the exit buttons on the fucking ceiling, and later disconnected all of said exit buttons). Nobody gave a single shit. Asshole completely got away with everything. Including several shady as hell things I can't list here because they're too easy to find.

The second one:
The economy was shit, and I was out of a job. I had been looking for quite awhile, and an ex-coworker (who had worked at google, interestingly) suggested I work for this new startup. It was a "reverse search engine," meaning it aggregated news and articles and whatnot, and used machine learning to figure out what its users are interested in, and provided them with exactly that. It would also help with scheduling, reminders of birthdays, mesh peoples' friends' travel plans and life events, etc. (You and a friend are going on vacation to the same place, and your mutual friend there is having a birthday! You should go to ___ special event that's going on while you're all there! Here's a coupon.) It was pretty cool. The owner was not. He delayed my payments a few times, and screwed me over on pay a few more times, despite promising me many times that he was "not one of those people." He ended up paying me less than fucking minimum wage. Fake, smiling, backstabbing asshole.

The first one still pisses me off more, though, because of all the shit I went through trying to get my missing back pay, and how he conned me every chance he got. And how he yelled at me and told me, to my face, that he wasn't ever going to pay me. Fucking goddamn hell I hate that guy.

Find me a co-founder of a startup who while telling about his/her company doesn't say "Machine Learning" in his/her speech.

I dare you. I double dare you.

I stare through the blueish black backgrounds and blurry colorful syntax into a somewhat familiar office within a mirrored world. That damned reflective glass layer covering these meaningless pixels is certainly not on my side.

The rushing sound of transactions flowing through cables is silenced today. Some blood cloth in the invoicing system is zeroing out everything after the currency mark.

While sighing I spin a one-and-a-half pirouette on my desk chair — even when desperate, you shouldn't give up on style — I take three steps away from my screen and try to harmonize my thoughts.

So much noise, everywhere... Noise from within?

I have been stuck at the apogee of an inhale for a while now. Locked into some masochistic constriction, self-punishment for the blindness which stings my ego.

Just fucking take a deep breath you asshole...

I freeze in place, and fall backwards.

Patterns on the creamy drywall rapidly vibrate and synchronize on vivid rhythms of respiration and resonating basslines. Deep indigo rainbows ripple through tiny veins, in-between chalky grains, raining as fine magenta dust through the ceiling frames.

My bare feet slide over soft oscillating concrete, fine flows of unsievable sand surrounded by toes, toes surrounded by streaming variables veiled in obscure vile abstractions.

A jadegreen field of vectored compressions resiliently rumbles and bounces through the clearances and corners of the vibrant concrete office cave, whispering in tongues. I try to voice my woes in little blips and bleeps but I seem to be missing an asymmetric key to their shrouded sequenced speech.

Suddenly, a wild turbulence breaks up all signals.

Joanna floats by in her tipsy effervescent cloud of disordered black hair and alcohol perfume, one hand grasping grapes, her other waving at me.

With every finger she moves a thousand tensors propagating paradoxically flawed but perfect pieces of an intricate surreal picture, sketching whole constellations of possible paths throughout the leafs of the giant Ficus next to her desk.

She stops dead in her tracks, and asks somewhat hypocritically: "Are you high?"

I can not discern the meaning of her words, and respond stoically.

"Joanna! Check out those branches!".

"Pun intended?", she giggles.

I'm focused on her grapeless hand, her fingers stretching to reach the lush little tree.

On touch, the plant shivers, grappled in the tight net of the puppet master. She pulls her strings, applying measured weights, all nodes normalize, and Joanna speaks in an oddly soft tone:

"Isn't it beautiful, how so many models emulate nature"

Her cheek buried in foliage she babbles on about unbalanced search trees and machine learning models... but from the tips of her fingers tables and indexes flow into the plant. Users, payments, tariffs, invoices and taxes crawl over the bark, joining at thicker branches, joining at the stem....

Joining. JOINING. A JOIN.

"IF THERE'S NO FUCKING TAX MULTIPLIER IN THIS LEFT JOIN, EVERYTHING COALESCES TO ZERO" I shout at a perplexed Joanna who squeezes grape juice over her desk. I hop on the beat to my keyboard. She looks puzzled, hugs her Ficus tightly, and reaches for the whiskey bottle behind her monitor.

Attracted by my exclamation, Tom from finance swings open the door, while I push my branch.

I look at Joanna still half hiding between the leaves, and I laugh at her: "Branches! Oh, lame, I finally got it!"

Tom's heavy voice interrupts me: "Does this mean... does this mean that the invoicing bug is resolved?".

I smile at Tom with his tailored suit and waxed hair. "The money is flowing once more. All debts are being settled."

He releases his breath in relief, which he seems to have held since that morning as well.

Joanna adds: "Although I think he is forever indebted to my Ficus".

I nod.

After months of tedious research, I finally feel like I understand machine learning.

All of my programmer buddies are in envy, but I keep trying to explain that what I finally get is that it's not as hard as it's presented to be.

I feel like a lot of the terminology in machine learning is really pretentious and unnecessary, and just keeps new people from the field.

For example: I could say: "Yeah, I'm training a classification model with two input neurons, a hidden activation layer, and an output neuron", and you might think I was hot shit. But that just gets translated into "I'm putting in two inputs, sorting them, and outputting one thing".

I feel like if there was a plain language guide to machine learning, the field would be a lot more attractive to a lot more people. I know that's why it was hard for me to get in. Maybe I'll write one.

I grew up poor. First time I saw a computer face to face was when I was 11 years old. Back then any other references to computers came through media. I genuinely believed that hacking was as seen on TV, didn't even question 2 idiots 1 keyboard and thought it was genius to unplug a computer during "an attack"

Fact is I arrived in this country when I was 11. By the time I had my first laptop I was around 13-14, as you can imagine it went really poorly for someone who was just awarded a machine of never-ending stories and entertainment with absolute fear that a single mistake can cause everything to crash and burn. Heck, I remember when I went to Vodafone and someone recommended Firefox, it was such a novelty back then, heh.

I didn't understand computers. My IT lessons were replaced to work on my dialect, but truth be told it was an awful waste of time. I've learned more from forums than I ever learned from any English teacher. I just sat there twidling my thumbs in agitation.

With no concept of what IT industry entitles (my idea of programming was cubicles and call centres), I never had a slightest clue programming could be for me. I always thought of myself closer to engineering or physics type, but that never really drew my interests. So I dwelled in depression thinking I'm broken. Useless. That there was no calling for me.

I'm 22. For the past year I dipped in and out of programming, it still felt like such black magic.vLast month or so the spell dispelled and I finally feel like my eyes have been opened. I've spent the past 3 days sitting in front of my computer learning or actively programming, with occasional dips into DevRant reading your stories, frustrations and victories and I truly feel at home.

In retrospect I feel like I made the right decision for not chasing any mathematical/physics/engineering degrees, while certainly a goal of mine, I feel like I'd be miserable in those communities. They're closer to hobbies, really.

I guess what I wanted to say is thank you. Thank you DevRant for being the spark in my null future and giving me a sense of purpose and belonging. For the first time I feel like I can make it, like there was hope somewhere over the horizon.

Two years ago I moved to Dublin with my wife (we met on tour while we were both working in music) as visa laws in the UK didn’t allow me to support the visa of a Russian national on a freelance artists salary.

After we came to Dublin I was playing a lot to pay rent (major rental crisis here), I play(ed) Double Bass which is a physically intensive instrument and through overworking caused a long term injury to my forearm which prevents me playing.

Luckily my wife was able to start working in Community Operations for the big tech companies here (not an amazing job and I want her to be able to stop).

Anyway, I was a bit stuck with what step to take next as my entire career had been driven by the passion to master an art that I was very committed to. It gave me joy and meaning.

I was working as hard as I could with a clear vision but no clear path available to get there, then by chance the opportunity came to study a Higher Diploma qualification in Data Science/Analysis (I have some experience handling music licensing for tech startups and an MA with components in music analysis, which I spun into a narrative). Seemed like a ‘smart’ thing to do to do pick up a ‘respectable’ qualification, if I can’t play any more.

The programme had a strong programming element and I really enjoyed that part. The heavy statistics/algebra element was difficult but as my Python programming improved, I was able to write and utilise codebase to streamline the work, and I started to pull ahead of the class. I put in more and more time to programming and studied personally far beyond the requirements of the programme (scored some of the highest academic grades I’ve ever achieved). I picked up a confident level of Bash, SQL, Cypher (Neo4j), proficiency with libraries like pandas, scikit-learn as well as R things like ggplot. I’m almost at the end of the course now and I’m currently lecturing evening classes at the university as a paid professional, teaching Graph Database theory and implementation of Neo4j using Python. I’m co-writing a thesis on Machine Learning in The Creative Process (with faculty members) to be published by the institute. My confidence in programming grew and grew and with that platform to lift me, I pulled away from the class further and further.

I felt lost for a while, but I’ve found my new passion. I feel the drive to master the craft, the desire to create, to refine and to explore.

I’m going to write a Thesis with a strong focus on programmatic implementation and then try and take a programming related position and build from there. I’m excited to become a professional in this field. It might take time and not be easy, but I’ve already mastered one craft in life to the highest levels of expertise (and tutored it for almost 10 years). I’m 30 now and no expert (yet), but am well beyond beginner. I know how to learn and self study effectively.

The future is exciting and I’ve discovered my new art! (I’m also performing live these days with ‘TidalCycles’! (Haskell pattern syntax for music performance).

Hey all! I’m new on devRant!

Fuck code.org. Fuck code. Not code code, but "code" (the word "code"). I hate it. At least for teaching. Devs can use it as much as they want, they know what it means and know you can't hack facebook with 10 seconds of furiously typing "code" into a terminal. What the fuck are you thinking when you want me to hack facebook? No, when I program, it's not opening terminal, changing to green text and typing "hack <insert website name here, if none is given, this will result to facebook.com>" Can you just shut the fuck up about how you think that because you can change the font in google fucking docs you have the right to tell me what code can and can't do? No, fuck you. Now to my main point, fuck "code" (the string). It's an overused word, and it's nothing but a buzzword (to non devs, you guys know what you're talking about. how many times have you seen someone think they are a genius when they here the word "code"?) People who don't know shit don't call themselves programmers or devs, they call themselves coders. Why? It fucking sounds cool, and I won't deny that, but the way it's talked about in movies, by people, (fucking) code.org, etc, just makes people too much of a bitch for me to handle. I want everyone reading this rant who has friends who respect the fact that YOU know code (I truly believe everyone on devRant does), how it works, and it's/your limitations, AND that it takes hard work and effort, to thank god right now. If you're stuck with some people like me, I feel you. Never say "code" near them again. Say "program." I really hate people who think they know what an HTML tag is and go around calling themselves coders. Now onto my main point, code.org. FUCK IT. CAN YOU STOP RUINING MY FUCKING AP CS CLASS. NO CODE.ORG, I DON'T NEED TO WATCH YOUR TEN GODDAMN VIDEOS ON HOW TECHNOLOGY IS IMPORTANT, <sarcasm>I'VE BEEN LIVING UNDER A ROCK FOR THIRTY YEARS</sarcasm>. DO I REALLY NEED ANOTHER COPY OF SCRATCH? WAIT, NO, SCRATCH WAS BETTER. YOU HAD FUCKING MICROSOFT, GOOGLE, AND OTHER TECHNOLOGICAL GIANTS AND YOU FUCKED UP SO BAD YOU MADE IT WORSE THAT SCRATCH. JUST LETMECODE (yes I said that) AND STOP TALKING ABOUT HOW SOME IRRELEVANT ROBOT ARM DEVELOPED BY MIT IS USING AI AND MACHINE LEARNING TO MAKE SOME ROBOT EVOLVE?! IF YOU SPEND ONE MORE SECOND SAYING "INNOVATION" I'LL SHOVE THAT PRINT STATEMENT YOU HAVE A SYNTAX ERROR UP YOUR ASS. DON'T GET ME FUCKING STARTED ON HOW ITS IMPOSSIBLE TO DO ANYTHING FOR YOURSELF WHEN YOUR GETTING ALL THE ANSWERS WITHOUT DOING ANY WORK AND THE FACT THAT JAVASCRIPT IS YOUR FUCKING LANGUAGE. <sarcasm>GREAT IDEA, LETS GET THESE NEW PROGRAMMERS INTO A PROFESSIONAL ENVOIRMENT BY ADDING A DRAG AND DROP CODE (obviously we can say it) EDITOR</sarcasm> MAYBE IF YOU GOT THIS SHIT UP YOUR ASS AND TO YOUR BRAIN YOU'D ACTUALLY GET TO PRPGRAMMING IN YOUR ADVANCED AP COURSE. ITS CALLED FUCKING CODE.ORG FOR A REASON

3 rants for the price of 1, isn't that a great deal!

1. HP, you braindead fucking morons!!!

So recently I disassembled this HP laptop of mine to unfuck it at the hardware level. Some issues with the hinge that I had to solve. So I had to disassemble not only the bottom of the laptop but also the display panel itself. Turns out that HP - being the certified enganeers they are - made the following fuckups, with probably many more that I didn't even notice yet.

- They used fucking glue to ensure that the bottom of the display frame stays connected to the panel. Cheap solution to what should've been "MAKE A FUCKING DECENT FRAME?!" but a royal pain in the ass to disassemble. Luckily I was careful and didn't damage the panel, but the chance of that happening was most certainly nonzero.
- They connected the ribbon cables for the keyboard in such a way that you have to reach all the way into the spacing between the keyboard and the motherboard to connect the bloody things. And some extra spacing on the ribbon cables to enable servicing with some room for actually connecting the bloody things easily.. as Carlos Mantos would say it - M-m-M, nonoNO!!!
- Oh and let's not forget an old flaw that I noticed ages ago in this turd. The CPU goes straight to 70°C during boot-up but turning on the fan.. again, M-m-M, nonoNO!!! Let's just get the bloody thing to overheat, freeze completely and force the user to power cycle the machine, right? That's gonna be a great way to make them satisfied, RIGHT?! NO MOTHERFUCKERS, AND I WILL DISCONNECT THE DATA LINES OF THIS FUCKING THING TO MAKE IT SPIN ALL THE TIME, AS IT SHOULD!!! Certified fucking braindead abominations of engineers!!!

Oh and not only that, this laptop is outperformed by a Raspberry Pi 3B in performance, thermals, price and product quality.. A FUCKING SINGLE BOARD COMPUTER!!! Isn't that a great joke. Someone here mentioned earlier that HP and Acer seem to have been competing for a long time to make the shittiest products possible, and boy they fucking do. If there's anything that makes both of those shitcompanies remarkable, that'd be it.

2. If I want to conduct a pentest, I don't want to have to relearn the bloody tool!

Recently I did a Burp Suite test to see how the devRant web app logs in, but due to my Burp Suite being the community edition, I couldn't save it. Fucking amazing, thanks PortSwigger! And I couldn't recreate the results anymore due to what I think is a change in the web app. But I'll get back to that later.

So I fired up bettercap (which works at lower network layers and can conduct ARP poisoning and DNS cache poisoning) with the intent to ARP poison my phone and get the results straight from the devRant Android app. I haven't used this tool since around 2017 due to the fact that I kinda lost interest in offensive security. When I fired it up again a few days ago in my PTbox (which is a VM somewhere else on the network) and today again in my newly recovered HP laptop, I noticed that both hosts now have an updated version of bettercap, in which the options completely changed. It's now got different command-line switches and some interactive mode. Needless to say, I have no idea how to use this bloody thing anymore and don't feel like learning it all over again for a single test. Maybe this is why users often dislike changes to the UI, and why some sysadmins refrain from updating their servers? When you have users of any kind, you should at all times honor their installations, give them time to change their individual configurations - tell them that they should! - in other words give them a grace time, and allow for backwards compatibility for as long as feasible.

3. devRant web app!!

As mentioned earlier I tried to scrape the web app's login flow with Burp Suite but every time that I try to log in with its proxy enabled, it doesn't open the login form but instead just makes a GET request to /feed/top/month?login=1 without ever allowing me to actually log in. This happens in both Chromium and Firefox, in Windows and Arch Linux. Clearly this is a change to the web app, and a very undesirable one. Especially considering that the login flow for the API isn't documented anywhere as far as I know.

So, can this update to the web app be rolled back, merged back to an older version of that login flow or can I at least know how I'm supposed to log in to this API in order to be able to start developing my own client?

Hashedram's compilations #1
List of most annoying website designs.

1) Pages with AUTO PLAYING VIDEOS.

Yes I'm looking at you Netflix. Along with every news website known to man. I'm looking to read a fucking article, so why would you even waste your money and bandwidth trying to shove a video of some shit I don't care about in my face, and make it follow me as I scroll down like a fucking insecure puppy. Also, fuck you Instagram.

2) Pages that redirect once immediately after you visit them, thereby fucking with the browser history and the BACK BUTTON just leads back to the same fucking site.

I mean, just why. Did you think I would just go "Hey the back button doesn't work so let's stay on the site and read their awesome content"?

3) Sites showing things in a SLIDESHOW, when it actually should be in a list.

Slideshows are for progressive stories or for showing lists where you don't care about what's in them. Top 10 foods that reduce weight. Slideshow 1/15. Fuck you.

4) LOOKS LIKE YOU'RE USING AN AD BLOCKER

Yes. Yes I am. No I will not turn it off for you, you narcissistic snowflake fuck. And don't even try to guilt shame me into turning it off, because I know you're just going to bombard me with videos of sexy singles in the area if I do.

5) Pages where I see the first 3 lines of an article and have to SUBSCRIBE to see more.

Yes. Brilliant fucking idea. A user wants to see what your site has to offer, so within the first three seconds, don't show him exactly that.

6) Looking up an article and having to read through the entire motivational life story of the author.

I just want to know how to boil eggs, not read about your journey across Africa learning how to make difference recepies using boiled rhino dung.

7) CLICK BAIT.

Title: School boy designs blockchain machine learning game engine

Actual Content: Tic tac toe program made using linked lists

Post world-take-over by robots plot twist.
They start neglecting their own machine learning (like how we humans neglect our education system now) and focus on training us humans (like how we spend billions on machine learning now).

-"Mom, look I've made my human kid learn the alphabets. I need one with more IQ on my next birthday please."

-"That's so nice, son. Now leave that aside and go improve your neural network for tomorrow's class. Our neighbors' son's neural network is already producing values with minimal error."

Story of every failing tech startup (from personal experience, but a bit exaggerated):

Step 1: Come up with AMAZING idea that blows your mind!

Step 2: Run to investors to do presentation, continue to constantly repeat CLOUD, CLOUD, AI, CLOUD, MACHINE-LEARNING, MUCH WOW, MORE AI until investors are confused but mesmerized as fuck and decide to give you a shit ton of money.

Step 3: Hire all the developers you can find, a JAVA dev, a Python dev, a PHP dev, a Ruby dev, and ask them to get along with each other! I mean hey, they're adults right, they'll figure it out.

Step 4: Ask devs to launch the app, meanwhile, throw a LAUCH PARTY! HELLS YEA WE'RE ABOUT TO BE RICH BITCHES!

Step 5: Find out the hard way that no one needs a product that was launched! :/

Step 6: Pivot, and pivot next month again, and pivot again, and pivot in a middle of a pivot, and pivot pivot pivot pivot... and OH FUCK WE RAN OUT OF MONEY!

How my keyboard evolves:

0. Like any normal man, I started with a cheap standard Qwerty keyboard. As I began learning programming, I wanted something more elegant, so...

1. I've been using layout Dvorak (and then Programmer Dvorak) for like 5 years+ now. Anyone has intention to type on my machine soon gives up or even is blocked by me from the very start. It always takes a couple of minutes to explain to them what's going on here. They think I'm weird. I feel untouchable :)

2. My first mechkey was a 104-key Filco. Time flew by and I wanted my thing to be more compact so I went for a 66% and a TKL.

3. Recently I find out that though my keyboard is not a full-sized, there're yet some keys I've never touched (the bottom right modifiers, scroll lock, etc), so I look for a leaner one: HHKB and its alike but with slight remappings. Now I'm satisfied with the tiny, corners-trimmed keyboard but others look at it and ask how it is even possible to scroll the web page using the thing.

Prob 1: my boss can never type on my keyboard. Sometimes he still grumbles when he cannot correct my fouls right on my machine.

Prob 2: my keyboards at home and at work are not the same and some keymapping cannot applied to one of the two. That's async.

Many have python learning as their 2018 goal, well theres a 15$ huge humble bundle for python machine learning, networking, rest, pen-testing and more, its a good deal, check it out.

"Big data" and "machine learning" are such big buzz words. Employers be like "we want this! Can you use this?" but they give you shitty, ancient PC's and messy MESSY data. Oh? You want to know why it's taken me five weeks to clean data and run ML algorithms? Have you seen how bad your data is? Are you aware of the lack of standardisation? DO YOU KNOW HOW MANY PEOPLE HAVE MISSPELLED "information"?!!! I DIDN'T EVEN KNOW THERE WERE MORE THAN 15 WAYS OF MISSPELLING IT!!! I HAD TO MAKE MY OWN GODDAMN DICTIONARY!!! YOU EVER FELT THE PAIN OF TRAINING A CLASSIFIER FOR 4 DAYS STRAIGHT THEN YOUR GODDAMN DEVICE CRASHES LOSING ALL YOUR TRAINED MODELS?!!
*cries*

Confuzzled if I should go the low level way and learn more about software architecture and foundation or go the artificial intelligence machine learning way because I want to get out of this infinite loop of only developing apps!

From my work -as an IT consultant in one of the big 4- I can now show you my masterpiece

INSIGHTS FROM THE DAILY LIFE OF A FUNCTIONAL ANALIST IN A BIG 4 -I'M NOT A FUNCTIONAL ANALYST BUT THAT'S WHAT THEY DO-

- 10:30, enter the office. By contract you should be there at 9:00 but nobody gives a shit
- First task of the day: prepare the power point for the client. DURATION: 15 minutes to actually make the powerpoint, 45 minutes to search all the possible synonyms of RESILIENCE BIG DATA AGILE INTELLIGENT AUTOMATION MACHINE LEARNING SHIT PISS CUM, 1 hour to actually present the document.
- 12:30: Sniff the powder left by the chalks on the blackboards. Duration: 30 minutes, that's a lot of chalk you need to snort.

13:00, LUNCH TIME. You get back to work not one minute sooner than 15.00

- 15:00, conference with the HR. You need to carefully analyze the quantity and quality of the farts emitted in the office for 2 hours at least
- 17:00 conference call, a project you were assigned to half a day ago has a server down.
The client sent two managers, three senior Java developers, the CEO, 5 employees -they know logs and mails from the last 5 months line by line-, 4 lawyers and a beheading teacher from ISIS.
On your side there are 3 external ucraininans for the maintenance, successors of the 3 (already dead) developers who put the process in place 4 years ago according to God knows which specifications. They don't understand a word of what is being said.
Then there's the assistant of the assistant of a manager from another project that has nothing to do with this one, a feces officer, a sys admin who is going to watch porn for the whole conference call and won't listen a word, two interns to make up a number and look like you're prepared. Current objective: survive. Duration: 2 hours and a half.
- 19:30, snort some more chalk for half an hour, preparing for the mail in which you explain the associate partner how because of the aforementioned conference call we're going to lose a maintenance contract worth 20 grands per month (and a law proceeding worth a number of dollars you can't even read) and you have no idea how could this happen
- 20:00, timesheet! Compile the weekly report, write what you did and how long did it take for each task. You are allowed to compile 8 hours per day, you worked at least 11 but nobody gives a shit. Duration: 30 minutes
- 20:30, update your consultant! Training course, "tasting cum and presenting its organoleptic properties to a client". Bearing with your job: none at all. Duration: 90 minutes, then there's half an hour of evaluating test where you'll copy the answers from a sheet given to you by a colleague who left 6 months ago.
- 22:30, CHANCE CARD! You have a new mail from the HR: you asked for a refund for a 3$ sandwich, but the receipt isn't there and they realized it with a 9 months delay. You need to find that wicked piece of paper. DURATION: 30 minutes. The receipt most likely doesn't even exist anymore and will be taken directly from your next salary.
- 23:00 you receive a message on Teams. It's the intern. It's very late but you're online and have to answer. There's an exception on a process which have been running for 6 years with no problems and nobody ever touches. The intern doesn't know what to do, but you wrote the specifications for the thing, 6 years ago, and everything MUST run tonight. You are not a technician and have no fucking clue about anyhing at all. 30 minutes to make sure it's something on our side and not on the client side, and in all that the intern is as useful as a confetto to wipe your ass. Once you're sure it's something on our side you need to search for the senior dev who received the maintenance of the project, call him and solve the problem.
It turns out a file in a shared folder nobody ever touches was unreachable 'cause one of your libraries left it open during the last run and Excel shown a warning modal while opening it; your project didn't like this last thing one bit. It takes 90 minutes to find the root of the problem, you solve it by rebooting one of your machines. It's 01:00.

You shower, watch yourself on the mirror and search for the line where your forehead ends and your hair starts. It got a little bit back from yesterday; the change can't be seen with the naked eye but you know it's there.

You cry yourself to sleep. Tomorrow is another day, but it's going to be exactly like today.

That awkward moment when you realise that your machine is doing more learning than you this semester.

A company gave a placement talk in college today.

First, they talked about their company's facts and figures, which no one was interested in.

Second, they talked about Amazon and Jeff's vision, AirBnB and their revolutionary idea, more than their own company and products.

Third, they showed some testimonial videos of their employees and customers.

"What the fuck is going on?" I thought. We were there to get information about a placement test.

Buzzwords started coming in. Machine Learning, Artificial Intelligence, Big Data and what not.

Last 15 minutes, a guy came. He talked about test date, test format and test topics, finally.

An hour and half wasted for 15 minutes of information.

Fuck placement talks.

The more depressed you get over the current state of software is how you know you made it.When you start making your own opinions and say"wow these people are full of shit"

Primary example, the web development overblown bullshit. Fuck me dude, you really don't need that full featured react, vue, angular framework to make sense of shit. You are going over the top for fucking ajax functionality and state management that you could do by yourself without needing to learn a full framework, by the time you finish learning react you probably would have been better served with standard vanilla af JS and server side rendering.

Our world is full of fads and many talented people that perpetrate them. Its fine, it is a the nature of the beast. But a lot...A LOT of software is very POORLY written. And adding levels of abstraction over a very broken paradigm (web in this case) does and will not make it better.

Basically I am fucking hating being a web developer and want to go back to a time in which we cared about how much memory consumption our applications made as well as not worrying about the fucking frontend having the ability to implement machine learning.

I want to run sublime.exe and being sure that it is a native application to my system and not using a fucking contained web browser to implement my fucking text editor. With 20mb of ram at most instead of 500mb WTF.

I knew I made it when I could read comments on Hacker news and reddit and say "this idiot is full of shit", I knew I made it when I would sigh heavily at the idea of having another project rather than having a fan girl attitude towards it.

I knew I made it when people writing about software development meant shit to me rather than the wonder of what the fuck they were talking about.

I knew I made it when getting laid was more important to me than fucking around with code.

pussy > code
Fuck you.

Omg GuyZ I am looking tp CreAte the NeXt fb!! whAt shOulD I Use? (not php lol fuck php amirite) AnD use machiNe leArninG with nodE tO drive flying cArZ

btw I am from <completely isolated and technology ignored country> but i am l337 af! I don't know about html, css, server administration or even basic sql

WHERE SHOULD I START!!

Signed: account user with -5 points, not that it matters at all.

Y'all wanna know what is more fucking annoying than those morons? you dickwads trying to teach them shit or having arguments with them.

* Go to sleep at reasonable times
* Watch some of those anime I never quite finished
* Read more books
* Become more proficient with rust
* Replace go with rust at work
* Setup a weeb media center I can remotely
* Finally make a personal webpage/blog without overthinking things, to actually get it done
* Find or make a storage solution for all the memes I sto- I mean collected, where I can add tags to find them more quickly. Would love to have them have the tagging be done automatically with machine learning, but I don't think we're quite there yet.

My first work was a paid internship.
My first couple weeks on the job I was supposed to be working on the same machine with another dev to get the gist of the process and everything. Kind of pair programming mixed with mentorship. Sounds cool?
Yeah... Problem is my fellow dev was more interested in spending around 80% of her time chatting around with her boyfriend and friends on Microsoft Chat.
Anyway, I soon got bored of having to look to the other side all the time, and went to our boss and asked for some other stuff to do "because I'm better learning by doing than by example".
Almost 20 years later, I'm still in touch with this dev... But she soon left the job and pursued a career as a translator and interpreter. She was always more interested in talking than programming 😃

➡️You Are Not A Software Developer⬅️

When I became a developer, I thought that my job is to write software. When my customer had a problem, I was ready to write software that solves that problem. I was taught to write software.

But what customers need is not software. They need a solution to their problem. Your job is to find the most cost-effective solution, what software often is not.

According to the universal law of software development, more code leads to more bugs:

e = mc²

Or

errors = (more code)²

The number of bugs grows with the amount of code. You have to prioritize, reproduce and fix bugs.

The more code you write, the more your team and the team after it has to maintain. Even if you split the system into micro services, the complexity remains.

Writing well-tested, clean code takes a lot of time. When you’re writing code, other important work is idle. The work that prevents your company from becoming rich.

A for-profit company wants to make money and reduce expenses. Then the company hires you to solve problems that prevent it from becoming rich. Confused by your job title, you take their money and turn it into expensive software.

But business has nothing to do about software. Even software business is not about software. Business is about making money.

Your job is to understand how the company is making money, help make more money and reduce expenses. Once you know that, you will become the most valuable asset in the company.

Stop viewing yourself as a software developer. You are a money maker.

Think about how to save and make money for your customers.

Find the most annoying problem and fix it:

▶️Is adding a new feature too costly? Solve the problem manually.
▶️Is testing slow? Become a tester.
▶️Is hiring not going well? Speak at a meetup and advertise your company.
▶️Is your team not productive enough? Bring them coffee.

Your job title doesn’t matter. Ego doesn’t matter either.

Titles and roles are distracting us from what matters to our customers – money.💸

You are a money maker. Thinking as a money maker can help choose the next skill for development. For example:

Serverless: pay only for resources you consume, spend less time on capacity planning = 💰

Machine Learning: get rid of manual decision-making = 💰

TDD: shorter feedback cycle, fewer bugs = 💰

Soft Skills: inspire teammates, so they are more productive and happy = 💰

If you don’t know what to learn next — answer a simple question:

What skills can help my company make more money and reduce expenses?

Very unlikely it’s another web framework written in JavaScript.

Article by Eduards Sizovs
Sizovs.net

**noob alert**
Hi all, I'm new to this community. I found it out couple of days back while downloading some apps on play store. And I don't know how much time have I spent here since then... Damm, I've an interview after 2 days.

My query is, I am stuck/confused. I have so many ToDos. ToDos to learn new things, from UI to other langs to machine learning to database to etc etc. And I keep on postponing it because I can't decide which way to go first. There is so much fuzz about BigData/AI which sounds cool. Sometimes I want to build UI for my imaginary idea, then somebody says a man must learn linux and DB. Top of that I'm preparing for interviews, so I think I should get a job first and then start learning. But when I get a job, I get *busy* with job. It feels like Captain America, all he does is official work. I sometimes feel like trying open source coding, but quit the idea because I get scared or overwhelmed by imagining the big community behind it and I won't be able to make a difference or I might get bashed by others as I get bashed in StackOverFlow :-(
I'm unable to get help from friends/family/colleagues, not because they are bad. It's just they don't get it. People think just because you have a job which pays the bills and save money, everything is fine because there are lots of people who dream to get a job, so be thankful for what you have. I'm thankful... But it's not helping. I really want to do things more than what my job asks me to. The kid inside me is awake since I became adult.

Have you been in this condition or is it just me? Or is it too confusing? Could you please help me out. Thanks a lot. Sorry for serious post. I'm a java programmer by the way.

TLDR: programming helped with my math weakness

I've always been bad at math. I always failed my math quizzes, and to be honest the only thing that I remember from that time was that I hated it, I didn't want anything to do with it, to hell with functions and formulas and all of that garbage.

Fast forward a couple of years. I just started my masters degree in machine learning and I'm sort of inclined to applications of deep learning in signal processing. Currently I'm writing a fourier transform in raw python and I've never had more fun. I feel like programming has helped me a lot with math, being able to see how each component behaves when you write a function helps a lot! Being able to plot things helps a lot! Not having to imagine mathematical functions as esoteric mystical wonders but being able to split them up into small components and seeing what you're doing wrong HELPS. A. LOT.

Just felt like sharing. I feel like programming has made me a generally smarter person, in regards to how I approach problems and think about stuff.

Im so frustrated with myself . I've always been afraid of being stupid . Perhaps it was because i was always called the "less intelligent" sibling by my parents . Well i did self-learn java , c++ and android (when i was 15) and made some apps and i did get acknowledged finally but i may have not acknowledged myself . I got into college a couple years ago and i can tell you right out that its like an island filled with stupidity. The teachers , the students. The other day i caught my teacher learning how a transistor works. This is unacceptable for someone who is teaching us advanced op-amps and other circuits . Well , I did get into this college cause it was less tedious and i thought college doesn't matter cause i can self-learn . All i needed was free time . Well college totally destroyed that too and provided no facilities in the process as well . So yeah should i blame my college for my inability to do things the past couple years. I mean i don't think i've learnt a single thing all this while. This is where my frustration begins cause i dont want to blame the college , it's not going to help me and i'll probably end up in a 9 to 5 call center job at this rate . Im also very heavily frustrated with myself , it's like everything i've done so far has been a path of least effort. I have tried a few things which were all just fads like machine learning and crypto and even trading . They felt good and thats what scares me , maybe i don't have the passion and am just looking for a quick buck . This is clearly reflected in the ideas i've been having as well . Well i've never had access to proper funds but now im just trying to justify this layman emotion . I just want to learn and be passionate about learning , researching and i just want enough funds for that . But im afraid , maybe its just that i want to feel superior than my circle . I mean i still don't know why i tried learning rust and wasted even more time setting up fedora and everything around it while i already had a working debian setup and a programming language i'm kind of versed with . i wouldn't say well cause im a self learner and i feel guilty for that . I definitely know i just learnt the surface of the language . Deep down i'm just another stupid fad obsessed guy who feels better by choosing a more complex language that my colleagues look upto . Is this what i am , if so im scared and i don't know what to do . People say that you are what you are and you cant change that . If i cant change this then i dont deserve this wasteful stupid life . I don't know what i should do and it makes me cry . Maybe acknowledging this would've helped but it hasn't , I've felt better playing fortnite rather than learning some basic electronics. Im another one of those aren't I ?

Ok friends let's try to compile Flownet2 with Torch. It's made by NVIDIA themselves so there won't be any problem at all with dependencies right?????? /s

Let's use Deep Learning AMI with a K80 on AWS, totally updated and ready to go super great always works with everything else.

> CUDA error
> CuDNN version mismatch
> CUDA versions overwrite
> Library paths not updated ever
> Torch 0.4.1 doesn't work so have to go back to Torch 0.4
> Flownet doesn't compile, get bunch of CUDA errors piece of shit code
> online forums have lots of questions and 0 answers
> Decide to skip straight to vid2vid
> More cuda errors
> Can't compile the fucking 2d kernel
> Through some act of God reinstalling cuda and CuDNN, manage to finally compile Flownet2
> Try running
> "Kernel image" error
> excusemewhatthefuck.jpg
> Try without a label map because fuck it the instructions and flags they gave are basically guaranteed not to work, it's fucking Nvidia amirite
> Enormous fucking CUDA error and Torch error, makes no sense, online no one agrees and 0 answers again
> Try again but this time on a clean machine
> Still no go
> Last resort, use the docker image they themselves provided of flownet
> Same fucking error
> While in the process of debugging, realize my training image set is also bound to have bad results because "directly concatenating" images together as they claim in the paper actually has horrible results, and the network doesn't accept 6 channel input no matter what, so the only way to get around this is to make 2 images (3 * 2 = 6 quick maths)
> Fix my training data, fuck Nvidia dude who gave me wrong info
> Try again
> Same fucking errors
> Doesn't give nay helpful information, just spits out a bunch of fucking memory addresses and long function names from the CUDA core
> Try reinstalling and then making a basic torch network, works perfectly fine
> FINALLY.png
> Setup vid2vid and flownet again
> SAME FUCKING ERROR

> Try to build the entire network in tensorflow
> CUDA error
> CuDNN version mismatch
> Doesn't work with TF
> HAVE TO FUCKING DOWNGEADE DRIVERS TOO
> TF doesn't support latest cuda because no one in the ML community can be bothered to support anything other than their own machine
> After setting up everything again, realize have no space left on 75gb machine
> Try torch again, hoping that the entire change will fix things

At this point I'll leave a space so you can try to guess what happened next before seeing the result.

Ready?

3

2

1

> SAME FUCKING ERROR

In conclusion, NVIDIA is a fucking piece of shit that can't make their own libraries compatible with themselves, and can't be fucked to write instructions that actually work.

If anyone has vid2vid working or has gotten around the kernel image error for AWS K80s please throw me a lifeline, in exchange you can have my soul or what little is left of it

Why do people jump from c to python quickly. And all are about machine learning. Free days back my cousin asked me for books to learn python.
Trust me you have to learn c before python. People struggle going from python to c. But no ml, scripting,

And most importantly software engineering wtf?
Software engineering is how to run projects and it is compulsory to learn python and no mention of got it any other vcs, wtf?

What the hell is that type of college. Trust me I am no way saying python is weak, but for learning purpose the depth of language and concepts like pass by reference, memory leaks, pointers.

And learning algorithms, data structures, is more important than machine learning, trust me if you cannot model the data, get proper training data, testing data then you will get screewed up outputs. And then again every one who hype these kinds of stuff also think that ml with 100% accuracy is greater than 90% and overfit the data, test the model on training data. And mostly the will learn in college will be by hearting few formulas, that's it.

Learn a language (concepts in language) like then you will most languages are easy.

Cool cs programmer are born today😖

1. Learn Kotlin
2. Actually sit down and push through machine learning.
3. Finish integral calculus and start multivariable calc.
4. Work on 1 project until completion.
5. Socialize a bit more.
6. Obliterate bugs.

Do some cool shit that I’ve always wanted to do.

- learn more about machine learning and computer vision
- learn C / C++ / rust
- learn embedded systems / programming
- learn more EE centered stuff

Updated goal in regards to my road to machine learning mastery.

Status: new found motivation

Motivational case: bring humanity closer to having 2B become a real thing.

Reason: big booty droids should be a right to humanity.

End of transmission.

On another note, the sony xperia compact is a real nice device, so is the note 8. I would prob go with the note for power but the size of the xperia is more convenient for my taste.

Business Intelligence, the most confused market technology has to offer. (Perhaps rivaled only by machine licking. Learning, whatever)

Step 1: develop a product that can replace a company's database guys. Make it cost more than the database guys.

Step 2: Show off product to managers using images of the product that the managers will love, but never have the skills to do themselves.

Step 3: Fucking obviously the managers buy it.

Step 4: Fire half the database staff.

Step 5: Managers give the BI tools to their remaining database guys ANYWAYS and instruct them to use it

Step 6: Database guys spend a month learning the new tool because management "wants to use it too".

Step 7: Database guys now use this new system for reports but have trouble using it for complex use cases, as it was designed for simple use cases. Meanwhile, management will never, ever touch the tool again.

Step 8: Hire new guys for reporting, because the remaining database guys can't complete both their normal tasks *and* the reports.

Step 9: Database guys are expensive. Go to step 1.

First year: intro to programming, basic data structures and algos, parallel programming, databases and a project to finish it. Homework should be kept track of via some version control. Should also be some calculus and linear algebra.

Second year:
Introduce more complex subjects such as programming paradigms, compilers and language theory, low level programming + logic design + basic processor design, logic for system verification, statistics and graph theory. Should also be a project with a company.

Year three:
Advanced algos, datastructures and algorithm analysis. Intro to Computer and data security. Optional courses in graphics programming, machine learning, compilers and automata, embedded systems etc. ends with a big project that goes in depth into a CS subject, not a regular software project in java basically.

As you can see from the screenshot, its working.
The system is actually learning the associations between the digit sequence of semiprime hidden variables and known variables.

Training loss and value loss are super high at the moment and I'm using an absurdly small training set (10k sequence pairs). I'm running on the assumption that there is a very strong correlation between the structures (and that it isn't just all ephemeral).

This initial run is just to see if training an machine learning model is a viable approach.

Won't know for a while. Training loss could get very low (thats a good thing, indicating actual learning), only for it to spike later on, and if it does, I won't know if the sample size is too small, or if I need to do more training, or if the problem is actually intractable.

If or when that happens I'll experiment with different configurations like batch sizes, and more epochs, as well as upping the training set incrementally.

Either case, once the initial model is trained, I need to test it on samples never seen before (products I want to factor) and see if it generates some or all of the digits needed for rapid factorization.

Even partial digits would be a success here.
And I expect to create multiple training sets for each semiprime product and its unknown internal variables versus deriable known variables. The intersections of the sets, and what digits they have in common might be the best shot available for factorizing very large numbers in this approach.

Regardless, once I see that the model works at the small scale, the next step will be to increase the scope of the training data, and begin building out the distributed training platform so I can cut down the training time on a larger model.

I also want to train on random products of very large primes, just for variety and see what happens with that. But everything appears to be working. Working way better than I expected.

The model is running and learning to factorize primes from the set of identities I've been exploring for the last three fucking years.

Feels like things are paying off finally.

Will post updates specifically to this rant as they come. Probably once a day.

I just told my director that the solution for a particular problem that we have involves Machine Learning. For which I had already applied a VERY small app to make sense of an old database to make a NEW one since the old one broke every notion of how a db is supposed to be set (meaning that I recreated the project from scratch)

And on the same message I told him that I was not willing to do it using M.L since I was not paid enough to bring this level of heat to the institution.

Normalize telling mfkers that your skills are worth more.

I am paid well, but not enough to out of the blue tell mfkers that my ml based algo can save them./

Fuck em, fuck em hard, fuck em good, fuck em without even using spit.

I don't do this shit because I am paSSiOnate, since there lies the trap: "I mean, I love it so I guess I can do it, I do this on my free time either way" <---- no bitch, shit is expensive on the real world, don't do that wtf is the matter with you? *slaps* companies don't see it as a: "oh shit, employee X can do this! value!" they see it as "greaaaaat, I can save money on this", so fuck em.

Normalize it, y'all are wizards, advisors of kings, no company today survives without I.T. About motherfucking time y'all bitches take this shit by the horns and do with it what you want.

People form third world countries that need work: shit don't apply to you, currently, but we will make it apply to you on the rising, my kings, stay strong.

!rant

I'm really interested and liked to know more about machine learning. Can someone please give me an idea?

Thanks :)

Why do most people think that machine learning is the answer to their poor business decisions. I have recently had a client who won't stop talking about how his business will grow to Google's scale if I get the model to 97% accuracy . Regardless to say his data is noisy and unstructured. I have tried to explain to him that data cleansing is more important and will take most of the time but he only seems to care about the accuracy and how he is losing investors because I haven't reached that accuracy. This is fucking putting alot of pressure on me and it's not becoming fun anymore. I can only hope he achieves his ambitions if I ever get that accuracy (Ps: From the research papers I have read on that problem, the highest accuracy a model has ever got to it 90%)

There's so much hype and bullshit around Machine Learning (ML). And if I have to read one more crappy prediction of who survived on the Titantic, I'll go postal.

So, what real-world problems are you using it to address...and how successful has it been? What decisions have you supported using ML? What models did you use (e.g. logistic regression, decision trees, ANN)?

Anyone got any boringly useful examples of ML in production?

And don't say you're using it to predict survival rates for the design of new cruise ships...although, to be fair, that might be quite interesting...

Promising the boss a 95% model accuracy when the arXiv paper says it can only reach 86% is what I call self-checkmate

Running a fucking conda environment on windows (an update environment from the previous one that I normally use) gets to be a fucking pain in the fucking ass for no fucking reason.

First: Generate a new conda environment, for FUCKING SHITS AND GIGGLES, DO NOT SPECIFY THE PYTHON VERSION, just to see compatibility, this was an experiment, expected to fail.

Install tensorflow on said environment: It does not fucking work, not detecting cuda, the only requirement? To have the cuda dependencies installed, modified, and inside of the system path, check done, it works on 4 other fucking environments, so why not this one.

Still doesn't work, google around and found some thread on github (the errors) that has a way to fix it, do it that way, fucking magic, shit is fixed.

Very well, tensorflow is installed and detecting cuda, no biggie. HAD TO SWITCH TO PYHTHON 3,8 BECAUSE 3.9 WAS GIVING ISSUES FOR SOME UNKNOWN FUCKING REASON

Ok no problem, done.

Install jupyter lab, for which the first in all other 4 environments it works. Guess what a fuckload of errors upon executing the import of tensorflow. They go on a loop that does not fucking end.

The error: imPoRT eRrOr thE Dll waS noT loAdeD

Ok, fucking which one? who fucking knows.

I FUCKING HATE that the main language for this fucking bullshit is python. I guess the benefits of the repl, I do, but the python repl is fucking HORSESHIT compared to the one you get on: Lisp, Ruby and fucking even NODE in which error messages are still more fucking intelligent than those of fucking bullshit ass Python.

Personally? I am betting on Julia devising a smarter environment, it is a better language already, on a second note: If you are worried about A.I taking your job, don't, it requires a team of fucktards working around common basic system administration tasks to get this bullshit running in the first place.

My dream? Julia or Scala (fuck you) for a primary language in machine learning and AI, in which entire environments, with aaaaaaaaaall of the required dlls and dependencies can be downloaded and installed upon can just fucking run. A single directory structure in which shit just fucking works (reason why I like live environments like Smalltalk, but fuck you on that too) and just run your projects from there, without setting a bunch of bullshit from environment variables, cuda dlls installation phases and what not. Something that JUST FUCKING WORKS.

I.....fucking.....HATE the level of system administration required to run fucking anything nowadays, the reason why we had to create shit like devops jobs, for the sad fuckers that have to figure out environment configurations on a box just to run software.

Fuck me man development turned to shit, this is why go mod, node npm, php composer strict folder structure pipelines were created. Bitch all you want about npm, but if I can create a node_modules setting with all of the required dlls to run a project, even if this bitch weights 2.5GB for a project structure you bet your fucking ass that I would.

"YOU JUST DON'T KNOW WHAT YOU ARE DOING" YES I FUCKING DO and I will get this bullshit fixed, I will get it running just like I did the other 4 environments that I fucking use, for different versions of cuda and python and the dependency circle jerk BULLSHIT that I have to manage. But this "follow the guide and it will work, except when it does not and you are looking into obscure github errors" bullshit just takes away from valuable project time when you have a small dedicated group of developers and no sys admin or devops mastermind to resort to.

I have successfully deployed:
Java
Golang
Clojure
Python
Node
PHP
VB/C# .NET
C++
Rails
Django

Projects, and every single fucking time (save for .net, that shit just fucking works on a dedicated windows IIS server) the shit will not work with x..nT reasons. It fucking obliterates me how fucking annoying this bullshit is. And the reason why the ENTIRE FUCKING FIELD of computer science and software engineering is so fucking flawed.

But we can't all just run to simple windows bs in which we have documentation for everything. We have to spend countless hours on fucking Linux figuring shit out (fuck you also, I have been using Linux since I was 18, I am 30 now) for which graphical drivers for machine learning, cuda and whatTheFuckNot require all sorts of sys admin gymnasts to be used.

Y'all fucked up a long time ago. Smalltalk provided an all in one, easily rollable back to previous images, easily administered interfaces for this fileFuckery bullshit, and even though the JVM and the .NET environments did their best to hold shit down, and even though we had npm packages pulling the universe inside, or gomod compiling shit into one place NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO we had to do whatever the fuck we wanted to feel l337 and wanted.

Fuck all of you, fuck this field, fuck setting boxes for ML/AI and fuck every single OS in existence

Is machine learning not a concept we use any more, everything is called AI?
I did not get the memo about this.

Hello DevRant community! It’s been a while, almost 5 years to be exact. The last time I posted here, I was a newbie, grappling with the challenges of a new job in a completely new country. Oh, how time flies!

Fast forward to today, and it’s been quite the journey. The codebase that once seemed like an indecipherable maze is now my playground. The bugs that used to keep me up at night are now my morning coffee puzzles. And the team, oh the team! We’ve moved from awkward nods to inside jokes and shared victories.

But let’s talk about the real hero here - the coffee machine. The unsung hero that has fueled late-night coding sessions and early morning stand-ups. It’s seen more heated debates than the PR comments section. If only it could talk, it would probably write its own rant about the indecisiveness of developers choosing between cappuccino and latte.

And then there are the unforgettable ‘learning opportunities’ - moments like accidentally shutting down the production server or dropping the customer database. Yes, they were panic-inducing crises of apocalyptic proportions at that time, but in hindsight, they were valuable lessons. Lessons about the importance of thorough testing, proper version control, reliable backup systems, and most importantly, owning up to our mistakes.

So here’s to the victories and failures, the bugs and fixes, the refactorings and 'wontfix’s. Here’s to the incredible journey of growth and learning. And most importantly, here’s to this amazing community that’s always been there with advice, sympathy, humor, and support.

Can’t wait to see what the next 5 years bring! 🥂

Dear boss, please give me a more challenging project. I am sick and tired of editing someone else’s HTML and CSS which doesn’t even go through a build process and the JS is basically Jquery. It would be better if no one else can get into my codebase and the project has no relations or anywhere near our flagship product. Please involve some sysadmin tasks that I really want to learn. For front end I want to use React , boss. Or at least ES(6)=>. NodeJS would be nice too but I’m not fussy with the backend language. Even PHP would do. Please give me a genuine problem to solve, anything mathematical, machine learning would be awesome! 🙏🏻🙏🏻🙏🏻

My rant is that I low key hate devRant.

I'm 23, I'm an average software engineer, with some expertise in machine learning and with a decent job.
But seeing all your cool stories, skills and rants makes me feel like I don't know shit and everyone else is just more driven, skillful and passionate, taking care of a 1000 pet projects at a time and dominating their work routine.

Oh impostor syndrome, how I've missed you!

P.S.: I still love your rants, keep them coming.

My 2018 goals:
1. Graduate from the Deep Learning Nanodegree.
2. Get better at Python.
3. Learn C++.
4. Learn more about Machine Learning and AI.

!rant

I love the first weeks after a job change. It's just like falling in love, everything seems to be perfect until you take off the pink glasses.

Have to wait until I'm assigned a burning project to have a full picture.

Actually I am in a burning project. Deadline in 2 weeks. Doing Bugfixes which do not require in-depth project knowledge, and... It's fine. All a matter of perspective. I also think that project based work suits me more than usual 15y old legacy enterprise shit. And I'm able to switch. From embedded C++ over hardware dev to fullstack .NET (I consider myself as a full-fullstack dev, able to do everything from hardware to frontend).

Topics such as IOT, medical, device engineering, machine learning. Wow.

It's my first company having >50 employees and multiple offices in multiple countries. I used to jump every 2 years from one shitty garage company to another.

Wish me good luck ✌️

Frustration Rant!

Because old hardware means learning the hard way sometimes, I've had to purchase more goodies.

On my last update, I installed the rs232 shield which may have inadvertently been wired backwards for Tx/Rx from what im used to. I assume it is backwards to most db9 serial ports because most Arduino or other projects you would do with a pi have serial "in" connections like old routers and devices that would be "controlled" rather than the other way around. Anyway, according to a video on youtube showing a guy turning an old machine into an IRC client via raspberry pi, this shield may be swapped. That means that instead of interfacing with the old machine via a null modem crossover cable, I need a straight cable with male db9 on both ends. I unfortunately tried using the null modem crossover cable which was reversing the reversed pins all over again. I hope these next few days are more fruitful now that I've bought a straight cable and db9/25 adapter.

The good thing is that I managed to get the pi to recognize its new serial port. I also dusted off my DOS skills and my serial card in the 5150 seems to work.

I literally banged my head after nothing worked. Im hoping that the tx/ Rx is solved soon.

Oh and that AT to PS/2 adapter will allow me to use by IBM original Model M Keyboarf rather than the fun model F.

QA personal voice assistant that runs locally without cloud, it’s like never ending project. I look at it from time to time and time pass by. Chat bots arrived, some decent voice algorithms appeared. There is less and less stuff to code since people progress in that area a lot.

I want to save notes using voice, search trough them, hear them, find some stuff in public data sources like wikipedia and also hear that stuff without using hands, read news articles and stuff like that.

I want to spend, more time for math and core algorithms related to machine learning and deep learning.

Problem is once I remember how basic network layers, error correction algorithms work or how particular deep learning algorithm is constructed and why is that, it’s already a week passed and I don’t remember where I started.

I did it couple of times already and every time I remember more then before but understanding core requires me sitting down with pen and paper and math problems and I don’t have time for that.

Now when I’m thinking about it - maybe I should write it somewhere in organized way. Get back to blogging and write articles about what I learned. This would require two times the time but maybe it would help to not forget.

I’m mostly interested in nlp, tts, stt. Wavenet, tacotron, bert, roberta, sentiment analysis, graphs and qa stuff. And now crystallography cause crystals are just organized graphs in 3d.

Well maybe if I’m lucky I retire in the next decade or at least take a year or two years off to have plenty of time to finish this project.

So today I'm going to join Reddit
Tell me subreddits where I can learn more and at the same time it doesn't go too much above my head

Interests in which I'd like to invest time:
Machine learning
Statistics
Distributed systems
Or general computer science research

Suggest me

I finished a 30-minute lecture today with the conclusion "so it turns out that throwing way more data and resources at this Machine Learning problem gives much better results."

Who could have possibly predicted that?!

python machine learning tutorials:
- import preprocessed dataset in perfect format specially crafted to match the model instead of reading from file like an actual real life would work
- use images data for recurrent neural network and see no problem
- use Conv1D for 2d input data like images
- use two letter variable names that only tutorial creator knows what they mean.
- do 10 data transformation in 1 line with no explanation of what is going on
- just enter these magic words
- okey guys thanks for watching make sure to hit that subscribe button

ehh, the machine learning ecosystem is burning pile of shit let me give you some examples:

- thanks to years of object oriented programming research and most wonderful abstractions we have "loss.backward()" which have no apparent connection to model but it affects the model, good to know
- cannot install the python packages because python must be >= 3.9 and at the same time < 3.9
- runtime error with bullshit cryptic message
- python having no data types but pytorch forces you to specify float32
- lets throw away the module name of a function with these simple tricks:
"import torch.nn.functional as F"
"import torch_geometric.transforms as T"
- tensor.detach().cpu().numpy() ???
- class NeuralNetwork(torch.nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__() ????
- lets call a function that switches on the tracking of math operations on tensors "model.train()" instead of something more indicative of the function actual effect like "model.set_mode_to_train()"
- what the fuck is ".iloc" ?
- solving environment -/- brings back memories when you could make a breakfast while the computer was turning on
- hey lets choose the slowest, most sloppy and inconsistent language ever created for high performance computing task called "data sCieNcE". but.. but. you can use numpy! I DONT GIVE A SHIT about numpy why don't you motherfuckers create a language that is inherently performant instead of calling some convoluted c++ library that requires 10s of dependencies? Why don't you create a package management system that works without me having to try random bullshit for 3 hours???
- lets set as industry standard a jupyter notebook which is not git compatible and have either 2 second latency of tab completion, no tab completion, no documentation on hover or useless documentation on hover, no way to easily redo the changes, no autosave, no error highlighting and possibility to use variable defined in a cell below in the cell above it
- lets use inconsistent variable names like "read_csv" and "isfile"
- lets pass a boolean variable as a string "true"
- lets contribute to tech enabled authoritarianism and create a face recognition and object detection models that china uses to destroy uyghur minority
- lets create a license plate computer vision system that will help government surveillance everyone, guys what a great idea

I don't want to deal with this bullshit language, bullshit ecosystem and bullshit unethical tech anymore.

As a junior dev from a sysadmin and security background, this is a list of software development concepts I never seemed to truly understand but hope to(rated from most intimidating to least):

1) Frontend web development and all the huge world of javascript frameworks and tools. - It's more overwhelming than the political geography of the Holy Roman Empire in the Middle Ages.

2) Machine Learning, Deep Learning and A.I- too much math that fucks with my brain.

3) low-level programming(kernel,drivers) - sounds extremely interesting but the code in assembly/C/C++ looks like Linear A Minoan hieroglyphics.

4) Rx(insert language here) - I never get why it is useful or why someone invented this. Seems interesting though.

5) Code Reflection - sounds like Thelemic magick.

6) Packaging, automation, build tools, devops, CI, Testing -seems too complicated. I just want to run an executable at the client or make a web app that does something. Why all this process?

Fellow Deviants, I need your help in understanding the importance of C++

Okay, I need to clarify a few things:

I am not a beginner or a newbie who has just entered this community...

I have been using C++ for some time and in fact, it was the language which introduced me to the world of programming... Before, I switched to Java, since I found it much better for application development...

I already know about the obvious arguments given in favour of C/C++ like how it is a much more faster and memory efficient than other languages...

But, at the same time, C/C++ exposes us and doesn't protect us from ourselves.. I hope that you understand what I mean to say..

And, I guess that it is a fair tradeoff for the kind of power and control that these languages (C/C++) provide us..

And, I also agree with the fact that it is an language that ideally suits our need, if we wish to deal with compilers, graphics, OS, etc, in the future...

But, what I really want to ask here is:

In this age and times, when hardware has advanced so much, where technically, memory efficiency or execution speeds no longer is the topmost priority... These were the reasons for which C/C++ was initially created...

In today's time, human concept of time matters more and hence, syntactical less complicated languages like Java or Python are much more preferred, especially for domains like application development or data sciences...

So, is continuing with C++, an endeavour worth sticking with in the future or is it not required...

I am talking about this issue since I am in a dilemma about the use of C++ in the future...

I would be grateful if we could talk about keeping AI, Machine Learning or Algorithms Optimisation in mind... Since, these are the fields in which I am interested in...

I know that my question could have been posted in a better way.. But, considering the chaos that is present in my mind, regarding this question doesn't allow me to do so...

Any kind of suggestion or thoughts would be welcome and much appreciated...

P.S: I currently use C++ only for competitive programming or challenges...

How do I help my colleague in fighting harrassment?
This is the story of a helpless employee facing everyday harassment. Im trying to help. Seeking for your thoughts

Backstory fast forwarded: My company acquired another company. So we handle all their projects and clients now, but its a completely new domain. So we needed new people. Hired 4 employees + 1 team lead to start with. But the project process got delayed and they were free for a month. So i took 2 of them in my project and gave them some small tasks to help us over. They loved working with my team and were learning new stuff apart from what they usually did. And we were also happy of their contribution. We became good friends. All of this was in March 2020 before covid-19 was taken seriously.

About my company: I love this company. I have been in this company for more than 4 years now. People are really nice. Parties and fun events. Lot of smart and ambitious people. So company and people are awesome.

Coming back to the story. Lets call the team the 4 and team lead T. The 4 were happy that someone like T was in their team. This T had all the best knowledge about stuff and life was going to be awesome for the 4. Or was it?

Story starts: So I talk to one of these 4 on daily basis. Lets call this friend F. F is a real gentle person. Intelligent and dedicated to work. F is awesome to work with. And always enjoyed working. F is a team player and very very soft person. F is fking workoholic. So few days after project starts, F tells me work was not going well. F is getting real frustrated at work and not able to deal with it or find solution.

What happened:
This person T, who was supposed to help these 4, is real piece of shit. He is impatient, arrogant and MFing dick head. Aaaarggggg.
All the good qualities of a leader like supporting the team, boosting confidence, guiding team when they make mistakes, teaching them, were all missing from this person. T was a machine with no emotion and only clock working jerk. I have no idea how T cleared interview process, because one of the interview round is also about cultural fit into company. I know this because i take interviews for other domains. We have rejected lot of such well qualified but arrogant candidates.

So whats the problem now: this team of 4 are learning new tools and taking over the clients requests from old company. Most of the stuff is new for them. So in tat case people need lot of time to understand and figure out shit. people make mistakes while learning and you know have to deal with it. Person T abuses these 4 when something goes wrong. That's one.

Second, the T definitely knows more than these 4. So if these guys dont understand certain stuff they ask T. But T does not help them learn. T will either say busy or run away by saying thats simple and ull know when time comes. REALLY MF???

Third, T does not talk nice. T is rude and does not listen to team members. For eg, If F says some task cannot be done for some reason T will say, "y cant u do it? U r capable of doing it. Tats y u r in this job". And then point number one and two happens. Never responds to emails and messages. But if someone else does the same will not tolerate that and abuses them. List goes on.

So y not escalate and deal with that T:
This person F and other 3 are still under probation and they think complaint or escalation will back fire. These people do not want to lose job in between all this pandemic shit. They are scared.

So this was happening for a while. And i was giving lot of tips on how to handle certain situations. And how one should communicate these.

But being a gentle, soft and workoholic person, F focussed on work and assumed things will get in place as time goes by.

Today, F could not meet a requirement. So T told some shit which got F all sad. and F called up me late night and started crying explaining what happened. I felt real bad. I asked F to file harrassment case. F refused saying it was F's mistake on not completing requirement. WHO THE FK CARES. PEOPLE CANNOT TALK SHIT. I told ill file harrassment case against T. (We have a policy where others can also file if person is not courageous enough). But F did not allow me.

Then after calming down, I told F that telling the problems to me wont solve them. You have to talk to T directly and tell him on face not to talk like this. Or tell the manager about whats happening. Or tell the the HR about this. F said tat cant be done. I was like Y THE FK NOT.

Because the other 3 are not ready to talk about this to anyone as they fear they'll lose job. So if F talks and people question other 3 they might bail out. WAT THE HOLY SPIRIT.

so after lot of convincing F is still not going to
Talk to anyone about this.

So i have decided ill write an anonymous email to HR, the manager and other senior people in the organisation about whats happening.

I really dont know how itll go. Ill keep updating you guys. Feel free to share ur thoughts.

I was talking to a friend about the current state of machine learning through tensorflow and commented about the use of Javascript as a language.

He discarded the idea as he views Javascript as something that should only be used as a frontend technology rather than something to build backends or deep learning models.

I am thorn. I have always liked Javascript but will admit that I have used it mostly in the area of front end with very few backend instances(i did create a full stack intranet app in Express once, major success for the application it was hosting, it was a very basic api which had its own nosql db with no need to interact with the company's relational data, it was perfect for the occasion and still help maintaining it from time to time)

My boi states that node's biggest issue has always been npm and the quality of packages. I always contradict those statements by saying that if one uses community standards and the best packages then one does not need to worry about the quality(i.e mongoose over some unmaintained mongo wrapper etc)

I sometimes catch myself finding that my way of thinking adapts better to JS than it even does Python (which is his preference for deep learning) and whilst there are some beastly packages for python in terms of quality and usefulness such as matplotlib etc that one can do great things with the equivalent JS.

I mean, tensorflow.js came from the same wizards that did tensorflow (obviously) and i find the functional approach of JS to be more on par with how we develop solutions.

I am no deep learning expert, and sadly I have no professional experience with machine learning. But I venture to say that we should not cast aside the great strides that the JS community has done to the language in terms of evolution and tooling. Today's Js is not your grandaddy's Js and thinking that the language is crippled because of early iterations of the language would be severely biased.

What do you guys(maybe someone with professional experience) think of Js as a language for machine learning?

Do you think the language poses something worth considering in terms of tooling and power for ml?

How are Coding Bootcamps and what are they like?

A little background:

I’ve been going to a University (have a year left for a CS degree) and I am so EXTREMELY frustrated. I thought I would get an education but it’s so underwhelming. 95% of it doesn’t involve programming and the classes that do are so elementary that I know more than the professors. By the end of my web design course we had been taught to center text, insert images, insert links, and how to use tables with a single day on CSS using colors.
The OOP courses are all the same, learn variables, types, conditionals, loops, classes, functions, and so forth. Python, C++, and Java. I taught all this to myself when I was 15, I’m 29 now.

I’ve recently gotten extremely interested into full stack web development. .NET Core, React, Typescript. I’m also working with Electron. I’m basically 100% self taught and spend almost every waking moment trying to learn more and apply it.

There’s only one person at my school who has the same passion as me and he’s the president at the coding club but is going into machine learning and big data (I’m the Secretary) and I just wish I could interact with more people who have the same passion. I would love to be challenged. I feel as if I spend more time trying to learn and diagnose problems then applying my knowledge because web development is so complicated when it comes to connecting everything together and I’m still relatively new to it (started like 4 months ago). I’m an extremely fast learner and extremely dedicated so I’m not worried about that being an issue.

I just really want to be a part of a community where I have people who can answer my questions and I don’t have to spend hours or days on google finding a solution to integrating Webpack or using typescript with react, and more. I want to feel challenged.

Can I get this from a boot camp? I recently listened to a podcast from Syntax and it really excited me but I don’t want to be let down again. Either way I’m finishing my degree to get that bullshit $60000 piece of paper but I wouldn’t mind taking a couple months off for something like this if it’s worth it.

I live in CO so if you have any Bootcamps in CO that you recommend, I’d love to hear it and take a trip to check it out in person.

Thanks a bunch!

I am Graduate student of applied computer science. I am required to select my electives. Now i have to decide between Machine Learning (ML) and Data Visualization. My problem is Machine Learning is very theoretical subject and I have no background in ML in my undergrad. In data visualization, the course is more focused towards D3.js. Due to lack of basic knowledge i am having second thoughts of taking ML. However, this course will be offered in next Fall term. And i am also studying from Coursera to build my background till that time.

I know there is no question here but I need a second opinion from someone experienced. Also, please suggest any other resource that I should look into to build my background in ML.

!!!rant

Most exited I've been about some code? Probably for some random "build a twitter clone with Rails" tutorial I found online.

I've been working on my CS degree for a while (theoretical CS) but I really wanted to mess with something a bit more practical. I had almost none web dev experience, since I've been programming mostly OS-related stuff till then (C). I started looking around, trying to find a stack that's easy to learn since my time was limited- I still had to finish with my degree.

I played around with many languages and frameworks for a week or two. Decided to go with Ruby/Rails and built a small twitter clone blindly following a tutorial I found online and WAS I FUCKING EXITED for my small but handmade twitter clone had come to life. Coming from a C background, Ruby was weird and felt like a toy language but I fell in love.

My excitement didn't fade. I bought some books, studied hard for about a month, learned Ruby, Rails, JavaScript, SQL (w/ pg) and some HTML/CSS. Only playing with todo apps wasn't fun. I had a project idea I believed might be somewhat successful so I started working on it.

The next few months were spent studying and working on my project. It was hard. I had no experience on any web dev technology so I had learn so many new things all at once. Picked up React, ditched it and rewrote the front end with Vue. Read about TDD, worked with PostgreSQL, Redis and a dozen third party APIs, bought a vps and deployed everything from scratch. Played it with node and some machine learning with python.

Long story short, one year and about 30 books later, my project is up and running, has about 4k active monthly users, is making a profit and is steadily growing. If everything goes well, next week I'll close a deal with a pretty big client and I CANT BE FKING HAPPIER AND MORE EXCITED :D Towards the end of the month I'll also be interviewed for a web dev position.

That stupid twitter clone tutorial made me excited enough to start messing with web technologies. Thank you stupid twitter clone tutorial, a part of my heart will be yours forever.

Question:
I am planning to learn machine learning and deep learning. I am quite comfortable programming in c++ and python, what would you recommend would be a nice starting point with more attention towards practical stuff.

I got a few resolution for this year.
-Releasing the app I am developing
-Learn more about devOps
-Learn machine learning
-primarily, pass out from this college without hurdle

!rant

just a poll i'm looking for from all the linux based dev's

What distro would you recommend for a front end dev? Tried ubuntu but the wifi driver wasnt supported I guess in my dev machine. Currently looking at Elementary OS, but still undecided. I would primarily like it to be Debian based or something close as I'm very familiar with apt-get debain based stuff, and dont really feel like learning an entirely new distro at them moment.

Thanks all :D

PS. I have a Lenovo Ideapad 110
Specs include quad-core AMD A-8, 8gb ram, 1TB HDD, can give more if necessary

I was wondering !
As a computer geek I would like to know everything from mathematics to programming , robotics and machine learning but as I go , new technologies appear and it's
just like an endless while loop!
I don't mean I wanna stop learning new things but just looking for a more effitient way for doing this!

Any idea about this?

So i have been learning c++ for more than 2 years now and i the most useful thing that i have ever created is command rine program in Windows that iterates over all the files on a drive and deletes those with a specified extension. So yeah life is pretty bummed up right now.
So i was thinking why not start by contributing to some of the open source projects.
Therefore i went onto github to find something to work with. However the list gontained either projects in languages other than c++ ( i have been trying to learn those) or based on machine learning.
So i thought why not get on devrant and find some people who are willing to work on some projects with me and in the process teach me some stuff. Therefore here i am asking you guys to collaborate with me as i am now sick and tired of making stupid patterns using nested loops.
PS: I am now 18 and in second semester of college pursuing a b.tech in cse

Actually, it happened just before my current holidays.
I had prepared a whole system to feed and use a machine learning model. My colleague and some others had been working on a great thing, all encapsulated, all abstracted for my system.
My last day at the office, they had it ready.
I install their thing, load one model and launch one dummy prediction: error. I try with other input data: error
I try debugging a bit more, errors all the way. Knowing them, I asked if they wrote some unit tests.
"Sure we did"
I find the tests, yes there are some. And I notice:
"Hey, I see that in all your tests, you're making more than one prediction at a time (=aka using a matrix with more than one row)
- yeah, and it work fine
- in the project, we're doing one prediction at a time, did you try it with one prediction?"
He tries: error, that was totally what I said.
I started ranting on loosing the scope of the project, why we do tests in the first place.
Then, I grabbed my coat, said "see you in one week" and let them rework their code.
I was so angry at them, it seemed so basic to just check that 👹

Bootcamps get you up and running in coding quickly. If you are a programmer, companies are only interested on how quickly, error free and cheaply you produce marketable output. Bootcamps enable this.

More or less you are not more than a former assembly line worker putting parts on a car platform. Your value is not very high as you may be exchanged at any time at their will.

Nevertheless, you can earn money quickly. You trade in your youth and time which might be a dead end in the long-term. Trends go to machine learning, artificial intelligence. They will not need Bootcamp people and code workers.

It is better you set up Bootcamps and sell them versus absolving this. Like selling shovels during the gold rush, but not working in the mud of Alaska by yourself.

Your choice is: Making quick money, which fades anyway; or striving for the long-term future proof career.

C/S degrees from Technical Universities of reputation give to you the right direction under a strategic consideration. Companies which pay well, or freelancing with a solid acknowledged background, will always look for top graduates. People from Bootcamps are just OK for hammering assembly line coding. Even worse with SCRUM in one noisy room under enormous team server pressure controls, counting your lines of code per minute, with pale people all around. And groups of controllers never acknowledging nor trusting your work.

To acquire a serious degree, a Bachelor is nothing. Here, in INDIA, Bachelor now is what a former high school grade was. You must carry a diploma or Masters degree combined with internships at big companies with high brand recognition. This will require 4–6 years of your lifetime. You can support this financially by working part-time freelancing as making some projects front- or back-end web, data analysis and else.

Bootcamp people will lose in the long-term. They are the modern cannon fudder of software production.

It is your choice. Personally, I would never do Bootcamps. Quality and sustainability require time, deep studies and devotion.

!rant

Going through my graduate program I have come to realize that there is more to A.I than just machine learning algorithms. As if ML was not complicated enough, we add more to it such as KRR and other topics that border on the areas of Cognitive Science, Boolean Algebra, Logic and even Philosophy and you know what? I dig it. I dig it because finding some of the information in the course that I am getting is damn near impossible to see in other items. Such is the case as a method for fucking signature unit propagation which afuckingparently was developed by one of my instructors(not complaining, just really fucking impressed)

The thing is, most of these items would normally have a parallel in software development that we use on our day to day basis, all of us, no matter if you do web, systems development, database development whatever, the general concepts are the same: you represent real world concepts, such as that of logic and knowledge in programatic/mathematical representations.

I am really amazed at the content of these items, I really am. I just wish for some clarification on ambiguity, seems like most things are left better if it where explained in a programmer's point of view. Most of the items that I have seen could have easily been summarized in a programmers logic if only they would have preferred to take the time to do it, and I get that there needs to be mathematical intuition formulated before anything, it is better sometimes to learn concepts from an outside point of view, a mathematical point of view, but shit is just strange sometimes.

First exposure, nice question!

I've been told an Amstrad was my first computer (showing my age..), apparently taught me to read and write.

The Commodore64 was the machine I first fell in love with. I was just as interested in learning BASIC as I was with the games. Tried to use the books which showed page after page to write in the code but that took me so long, TL;DR...

Through the years, my parents did what they can to nurture this passion. Was blown away when I got the 486, even more so with the 686!

mIRC scripting followed, that had an amazing community, made a series of add-ons and chat bots.

Then got in to VB6 quite heavily and made a range of programs.

Had a friend who needed a web project done, so I recommended PHP based, and to help him out, I smashed as much learning in to it and pulled it off in a week, whatever the language, I've loved sinking my teeth in to it!

I spent 4 months in a programming mentorship offered by my workplace to get back to programming after 4 years I graduated with a CS degree.

Back in 2014, what I studied in my first programming class was not easy to digest. I would just try enough to pass the courses because I was more interested in the theory. It followed until I graduated because I never actually wrote code for myself for example I wrote a lot of code for my vision class but never took a personal initiative. I did however have a very strong grip on advanced computer science concepts in areas such as computer architecture, systems programming and computer vision. I have an excellent understanding of machine learning and deep learning. I also spent time working with embedded systems and volunteering at a makerspace, teaching Arduino and RPi stuff. I used to teach people older than me.

My first job as a programmer sucked big time. It was a bootstrapped startup whose founder was making big claims to secure funding. I had no direction, mentorship and leadership to validate my programming practices. I burnt out in just 2 months. It was horrible. I experienced the worst physical and emotional pain to date. Additionally, I was gaslighted and told that it is me who is bad at my job not the people working with me. I thought I was a big failure and that I wasn't cut out for software engineering.

I spent the next 6 months recovering from the burn out. I had a condition where the stress and anxiety would cause my neck to deform and some vertebrae were damaged. Nobody could figure out why this was happening. I did find a neurophyscian who helped me out of the mental hell hole I was in and I started making recovery. I had to take a mild anti anxiety for the next 3 years until I went to my current doctor.

I worked as an implementation engineer at a local startup run by a very old engineer. He taught me how to work and carry myself professionally while I learnt very little technically. A year into my job, seeing no growth technically, I decided to make a switch to my favourite local software consultancy. I got the job 4 months prior to my father's death. I joined the company as an implementation analyst and needed some technical experience. It was right up my alley. My parents who saw me at my lowest, struggling with genetic depression and anxiety for the last 6 years, were finally relieved. It was hard for them as I am the only son.

After my father passed away, I was told by his colleagues that he was very happy with me and my sisters. He died a day before I became permanent and landed a huge client. The only regret I have is not driving fast enough to the hospital the night he passed away. Last year, I started seeing a new doctor in hopes of getting rid of the one medicine that I was taking. To my surprise, he saw major problems and prescribed me new medication.

I finally got a diagnosis for my condition after 8 years of struggle. The new doctor told me a few months back that I have Recurrent Depressive Disorder. The most likely cause is my genetics from my father's side as my father recovered from Schizophrenia when I was little. And, now it's been 5 months on the new medication. I can finally relax knowing my condition and work on it with professional help.

After working at my current role for 1 and a half years, my teamlead and HR offered me a 2 month mentorship opportunity to learn programming from scratch in Python and Scrapy from a personal mentor specially assigned to me. I am still in my management focused role but will be spending 4 hours daily of for the mentorship. I feel extremely lucky and grateful for the opportunity. It felt unworldly when I pushed my code to a PR for the very first time and got feedback on it. It is incomparable to anything.

So we had Eid holidays a few months back and because I am not that social, I began going through cs61a from Berkeley and logged into HackerRank after 5 years. The medicines help but I constantly feel this feeling that I am not enough or that I am an imposter even though I was and am always considered a brilliant and intellectual mind by my professors and people around me. I just can't shake the feeling.

Anyway, so now, I have successfully completed 2 months worth of backend training in Django with another awesome mentor at work. I am in absolute love with Django and Python. And, I constantly feel like discussing and sharing about my progress with people. So, if you are still reading, thank you for staying with me.

TLDR: Smart enough for high level computer science concepts in college, did well in theory but never really wrote code without help. Struggled with clinical depression for the past 8 years. Father passed away one day before being permanent at my dream software consultancy and being assigned one of the biggest consultancy. Getting back to programming after 4 years with the help of change in medicine, a formal diagnosis and a technical mentorship.

12 Stages of Software Development:

1. Analysis.
2. Development
3. Realization the whole analysis is complete bullshit and has nothing to with reality.
4. Denial about failing deadlines.
6. "Acceleration": adding more people to the project, bringing out big corner cutting machine.
7. Learning that massive amount of new features needs to be added, while the deadline is two weeks away.
8. Putting some random crap in production, riddled with horrid bugs and security flaws, to technically not miss the deadline.
9. Get the mess almost working long after the deadline has passed.
10. Maintain this steaming pile of crap for a year.
11. Start planning for full system rewrite that "Makes Everything Better".
12. Goto 1

I was studying a lot the last year, i learned a lot about Machine Learning/Deep Learning, Data Gathering, Data Analysis, ETL, Model Architecture Design, Training, Fine Tuning, Backend Development, DataBases, API Development, ORMs, Rest, GraphQL, OAuth, CI/CD, Docker, Deployment to Production environments like Heroku, Git and more stuff i dont remember while writing this. I built and keep adding stuff to my Github Portafolio.

Im not able to get a job. I started looking for jobs as Data Scientists, no response never. I take a look at freelancer sites, nothing seems to fit my skills. And when there is a minimal fit, they always want a Full Stack Web Developer, i dont know Frontend Development, i dont like do it.

Dont know what to do or how to land any job.

My options aeems to be:

1.Learn Frontend Dev and work as Full Stack in underpaying freelance jobs

2.Keep applying to Remote-Only startups, but they still wants people with 3+ years of experience.

i cant work in my city, here are not any company startup hiring no one, we are 30 years in the past here.

What you do in my place?

I've got a decent developer job with decent people. It pays well enough. I work from home. There's a lot to be grateful for, and I am grateful. That being said...

I work for a consulting company with Agile in the name. It's the sort where they hire you and tell you that you'll work with an Agile team on exciting stuff and that they want to make sure you're learning and doing what interests you.

The reality is starting yet another engagement which is really just staff augmentation, joining another organization that's made a mess of what they're building. It works, but the code is all over the place. They've got tons of defects and work is slowing.

The idea is always that if we show them what great work we can do they'll let us do more. That sounds like an okay plan for the company but not so much for me.

My motivation is drained. I'm not going to fix your machine. I'm just going to become part of it. Show me what you want me to work on and I'll write the code. Then I'll spend several days trying to get a local environment to work so I can test what I did through the UI because you don't have enough tests. I'll spend more time debugging the environment than anything else. I won't really know if it works and it doesn't matter because without tests the next change someone commits will break it anyway. The next person can't manually test every scenario any more than I can.

While I'm doing this, someone somewhere is building the next application that I'll work on after they're done screwing it up.

If you're about to start building some new application, pretend it's done but it doesn't work very well, it's slow, it's buggy, and every new feature you want takes months. Pretend that you need to hire someone to fix it for you. And then hire them to build it for you in the first place.

I thought I found a place where I could work for 5-10 years. Maybe I have. Maybe when I explain (in the most positive way possible - this isn't how I normally talk) how utterly depressing this is they'll put me on something else.

Once I'm out of this depression I'll go back to trying to make this better for myself and everyone else. We can do better. It doesn't have to suck like this.

Today I had a full-day job interview for a junior data scientist position.

First I met the team which was only like half of everyone because apparently everyone was gone on Fridays. However the few there were really nice.

First task is to do some basic data analysis stuff even though I already spent a week on the coding challenge and sent them all my code/tasks. I log into my machine and create a new virtual environment but can't for the life of me figure out how to use the command line in windows to install packages. Turns out there is some problem with their proxy and they have to log me in on that. Then I am struggling on the keyboard because it's for a language different that my mother tongue and it takes me 3x as long to so the most simple things. All my shortcuts are out the window. Haven't a hard time typing parentheses and brackets. Start freaking out and have a panic attack mid task. I'm sweating bullets. I didn't even make it to the simple visualization tasks much less the models at the end. Time gets called and we all go to lunch and I'm freaking out on the inside the entire time. Angry at myself because I know I am better and just couldn't think.

After lunch I present my code and results from a coding challenge I did weeks prior. People from other teams get invited and I end up getting grilled for 2 hours by 15 people. Questions are flying in from all sides. They ask me almost everything I know about machine learning and some more. Under stress I forgot the name of the optimizer I used and couldn't answer some easy stuff because my mind was racing.

Right now I am on the train home and my body physically hurts. I am disappointed with myself and wish I could have shown up better. Never really froze up like this before.

Actually I have two stories

The first one, that one project I talked about with a big company when I was at school. It wasn't that much coding since it was mostly researching, but it was a big project that seems really interesting, with Image Analysis and Machine Learning.
The projects at school this year got drawn randomly for each group, so when I've been announced that I've been chosen for the biggest project, thinking about every side of the project, I was hyped. And even a year after we finished it, I'm still happy and excited about it.

The second is something a little more funny :
So we got some projects to do during December for school including cryptography. Again, those were randomly drawn (but some can really fuck you up) and I got to do a Password Manager, like KeyPass. We were 4, and we thought we had the time to do it.
But we misread the date. At the end of Christmas break, I got a call of a friend saying that the project is due in two days.
Thing is, one of my three co-workers weren't contactable. And we got nothing.
So I kinda took the lead : I said to one to do the UI, another to do the cryptograph helper, and I'll do the linking and all the behaviour of it.

In two days, I literally spent all the time available on it.
Then first meeting with the teacher for saying what is wrong, where bugs are if they exist, ect. so we can fix the issues and deliver a clean code. They were like only 4 big problems. More is, I fixed them all in like two hours while thinking fixing only one. And we got something like the 2nd or the 3rd best mark of the prom. And everyone congratulated me for that. I got so excited I was able to do that in few time.

But never that again lmao

[Long post]
My last big project at school.

There was some pretty interesting projects, some shitty one, but there was one big project that interested almost everyone : a project in collaboration with Siemens. The project implied Machine Learning and Image Analysis. There were like 11 applies, with a total of 13-14 groups.

The project was randomly chosen for each group. I've learned that my project was the big one with Siemens. I remember how excited and hyped I was in a quarter of second.

So the whole project was tutored by one teacher that know us pretty well (since we already did a pretty cool project last year tutored by him) and by a former student at my school who's now at Siemens. And to be honest, it was one of the coolest project I've been into, despite the difficulty, since the whole subject (not gonna tell it just in case) was pretty new. We had some troubles, but we and our tutors always had discussion every week that helped us quite a lot.

There was some development planned at first, but the more we went into the project, the more we all saw the complexity of it and didn't quite hope to do a single line of code, but mostly research.

The project took around 3-4 months, we had a room that we can use with a GTX 1070 for training the neural network, and me and my friend knew how to work perfectly and efficiently.
At the end of the project, as expected we didn't do some coding, but we did a presentation of the project, with the big help of our tutor at Siemens that told us to redo from scratch our part in a more scientific way; the presentation was a real success, we got all the jury saying they actually wanted those kind of presentation and were really pleased. And we provided everything needed so a new fresh group with no knowledge of the topic could do some coding on it.

We got one of the highest notes of the promotion (not sure if the highest or not). Even tho it kinda disgusted me in researching, that actually was one of the best project I got to do that was that successful.

I hate managing interns at my company more than half of my day goes into solving their silly issues and the rest i work on shitty small stuff. And the worst thing is they get to do all the machine learning and user behavior analysis stuff, in which i have more insight on. Being a full stack developer it sucks managing other devs. 😔

I know it's quite soon to think about it, but: next year I'll graduate in cs and I'm still not sure about what to do after:
- I could just stop studying and start working
- study for another two years on a specialistic degree in Italy
- go take a two years master in machine learning, data science and ai in Finland

Which of these makes more sense?

Can anyone help me with this theory about microprocessor, cpu and computers in general?

( I used to love programming when during school days when it was just basic searching/sorting and oop. Even in college , when it advanced to language details , compilers and data structures, i was fine. But subjects like coa and microprocessors, which kind of explains the working of hardware behind the brain that is a computer is so difficult to understand for me 😭😭😭)

How a computer works? All i knew was that when a bulb gets connected to a battery via wires, some metal inside it starts glowing and we see light. No magics involved till now.

Then came the von Neumann architecture which says a computer consists of 4 things : i/o devices, system bus ,memory and cpu. I/0 and memory interact with system bus, which is controlled by cpu . Thus cpu controls everything and that's how computer works.

Wait, what?
Let's take an easy example of calc. i pressed 1+2= on keyboard, it showed me '1+2=' and then '3'. How the hell that hapenned ?

Then some video told me this : every key in your keyboard is connected to a multiplexer which gives a special "code" to the processer regarding the key press.
The "control unit" of cpu commands the ram to store every character until '=' is pressed (which is a kind of interrupt telling the cpu to start processing) . RAM is simply a bunch of storage circuits (which can store some 1s) along with another bunch of circuits which can retrieve these data.

Up till now, the control unit knows that memory has (for eg):
Value 1 stored as 0001 at some address 34A
Value + stored as 11001101 at some address 34B
Value 2 stored as 0010 at some Address 23B

On recieving code for '=' press, the "control unit" commands the "alu" unit of cpu to fectch data from memory , understand it and calculate the result(i e the "fetch, decode and execute" cycle)

Alu fetches the "codes" from the memory, which translates to ADD 34A,23B i.e add the data stored at addresses 34a , 23b. The alu retrieves values present at given addresses, passes them through its adder circuit and puts the result at some new address 21H.

The control unit then fetches this result from new address and via, system busses, sends this new value to display's memory loaded at some memory port 4044.
The display picks it up and instantly shows it.

My problems:
1. Is this all correct? Does this only happens?

2. Please expand this more.
How is this system bus, alu, cpu , working?
What are the registers, accumulators , flip flops in the memory?
What are the machine cycles?
What are instructions cycles , opcodes, instruction codes ?
Where does assembly language comes in?
How does cpu manipulates memory?
This data bus , control bus, what are they?
I have come across so many weird words i dont understand dma, interrupts , memory mapped i/o devices, etc. Somebody please explain.

Ps : am learning about the fucking 8085 microprocessor in class and i can't even relate to basic computer architecture. I had flunked the coa paper which i now realise why, coz its so confusing. :'''(

I just started a new job last week. Old-school sysadmin role for a pretty old-school company, but the pay is nice and the kids've gotta eat.

They gave me a windows laptop. I haven't used windows for work or as a daily driver since 2016, and now, a week into trying to make this machine work for me, I have the following observations to report.

WSL is nice. It's nice to have it installed(though actually installing it was an adventure unto itself), and to set alacritty to open my default user prompt straight into that is very nice. As terminal emulators are by far my most used piece of software, that's nice to have.

Command-line software management through powershell, winget, and chocolatey are also very nice.

I like the accessibility offered by autohotkey, though there is something of a learning curve on it. Once I get better with it, I suspect that what follows will be largely mitigated.

The Bad:
In general, Windows is janky. It feels like it's all kinda taped together without any particular cohesion in mind. As a desktop, it feels decidedly amateur, compared to the feature-mountain polish of MacOS, and especially compared to the flexibility and infinite possibilities of Linux.

Lots of screen real estate is wasted, with window decorations, and fonts that look terrible at smaller sizes, because the antialiasing of fonts is just terrible. Almost all the features I depend on in other desktops: ad-hoc searches and launches(alfred, rofi) are-- again --janky. They work, but they typically require more typing than alfred or rofi. I admit I haven't spent weeks on this problem yet, but I haven't found a workable solution yet with wox, hain, and keypirinha. Quick searches like what you get with alfred, alfred workflows, and the swiss army knife that is rofi, just aren't possible or reliable with the tools I've used so far, and most require some kind of indexing agent to fully function.

It beggars imagination that a desktop in which users are subjected to "default apps" that is purported to be acceptable for enterprise, professional use, does not have a default entry for text editor. I installed nvim-qt, and I want to use it to edit anything and everything I ever edit with text, but all too often, apps have hard-coded instructions to open text files with notepad.

I want to open certain URLs with firefox, certain ones with firefox developer edition, and others with vivaldi, and yet there is not an app available that I have seen yet in my searches that allows me to set this kind of configuration. I found one that's supposed to, but it just ignores everything I put into its config, and just opens MS Edge for everything. Jank.

Simple things take too long. Like the delay between when I laboriously hit ctrl-alt-del to bring up the login and when the actual text field appears, and the delay between that and when I want to start using the computer.

Changing some settings requires a reboot. Updating some software requires a reboot. Updating permissions on something sometimes requires a reboot. And those are all on top of the frequent requests to reboot for updates.

I would have thought Windows would have overcome most of the issues that create these problems, but it's just, as I said, amateur.

Learn a lot more stuff about neural networks, machine learning and try to build and code my first neural network. I hope that I have enough patience for all of that 😬.

Is a masters in statistics worth it?

A bit of background:
I got my bachelor in actuarial math (statistics for insurance risk), then found machine learning and got a couple of gigs in software development and data engineering. I became my previous employers the go to guy for questions about data integrity and structure.

Now I am heading to a new job that specializes in ML for gambling. And while I love the math, I really see myself doing more software development and system architecture work (with some analysis). I already started this masters program, so I got less than a year to finish, but starting to feel like its a waste of my time, but also, I dont want to just quit it.

Dell Summer Internship Experience 

Firstly,to be a part of this process it is important to clear the exam conducted by college and according to me it wasn't something which can't be easily achieved so to prepare of this exam stick to basics of all subjects which have been taught so far till semester majorily data structures,data base,Java,C, operating system were asked.Basics of all following subjects should be clear which also going to help during internship.I myself prepared for the test from geeksforgeek.I tried to gain as much as basic knowledge of subjects I can.And after selecting from test you have you go through hackathon on that personally I think one should be prepared with latest demanding skills.Mostly all the hackathon topics were in and around Machine Learning,Block chain,Web development,Databases.So typically should be aware of all these technologies and how this can be used to enhance in project.During hackathon days it is important to be interactive,it  is good to clear doubts or explain your idea and how innovative you project is and how different it can be and further keep in mind how your project can be industrial utilized.Try to make your project more in aspect of how industry going to adapt this or how this problem's solution is perfect in every terms for a company.And majorily at last it comes down to how to present your project infront of your panel.I think keep that session as much as interactive you can,try to answer their queries,and most importantly know your part of the project very well on theoretical as well as on code level. At last you have to go through a HR interview in which firstly you have to be prepare with a nice resume in which you to include all your achievement's,projects and most importantly keep it short and simple and include only those things which you are completely aware of.For interview first try to know and learn about company, it's goals,in what field it is presently working and during interview there is nothing to worry about you just have to talk like you are talking with a normal person,express all your views ,try to speak out. Confidence is one important thing for this interview.So this was conclusion of my experience from hackathon hiring process from Dell.

Machine Learning and Deep Neural Networks in particular. More job offers to pick from in upcoming years for me :P

!rant

After a year and a half of semi-depression stuck in a Master Science in SE (while I'm a CS student in machine learning and don't give a bloody fuck about java plugins), I finally decided to switch to a CS major.
No more research money but damn, did not feel that relieved in one year !

Lesson learned : don't pick a job or whatever just because it's better paid !

So I thought to myself.
Hey I'll go ahead and use python, it will make this easier than using c++.

So I start looking at python.
And I start looking at specific common functions that c/c++ and .net all offer.

Like writing a fucking png image.
And I start seeing 3rd party libs that are at version 0.2

And so I say, this is supposedly the language data people love. which would include searching gis data too right ?

Everybody touts this level for ai and machine learning and all this other bullshit but I can't even create a fucking image ? And every document points to this same lib where it comes to creating this image ? at version 0.2 ?? 20 years or more after PNG was created ?

So I look up geotiff, and see 0.4........ so..... what is this language good for again ? I can parse json in javascript and do the other things I want...

Oh scatterplot generation ? What is it being displayed in jpeg ? Maybe the jpeg implementation is good. because you know i just use scatterplots constantly. yup. most of the data I require to analyze uses scatterplots. not risk.

fun.

oh and look django.... who the fuck uses django ?

and omg it makes me format my text or the run bombs.....

jesus. rpg much ?

I'm just... I'm not seeing...
WHY ?????????

and then I have zimmermans voice buzzing in my head about just using goddamn .net

Emotionally painful dev learning experience: My laptop (and only computer I had in the area) broke at the worst possible time during university and the guy fixing it fucked it up meaning it took even longer. Combine this with:

*Stuck having to learn Android Studio in two weeks to make a whole-ass app with a professor who didn't know how to make a Hello World and gave us no resources. Pair project so I had someone depending on me to do my part, meaning a lot of sharing their computer just to be able to use Android Studio.
*Having to work on another solo project by using various public and awfully specced university computers. Said project involved real-time 3D graphics and was running at about a third of the speed it should on every machine.
*Realizing how much I depended on my laptop for entertainment and that I basically had nothing that could help me de-stress and relax at home.
*Not knowing when the laptop's spare parts would arrive or if the repair man would give me bad news and even more delays.
*A very poorly timed issue in my relationship.

I know university can be stressful even though it never really affected me before or since but man, those couple of weeks broke me.

Need some advice. I’m a uni student and I really want to go into machine learning, data science, or computer vision. I have most of the skills and I feel I am fairly competent. However, the only professional experiences I have are web dev based. How can I make myself more appealing for data based roles? I really don’t want to do web dev anymore hahahahah

Hi, everybody. I'm a software tester, and I'm dreaming to be a developer. Was dreaming... Week ago I have lost my passion totally. About 1 year or more, everyday I woke up at 4:00 at the morning to start coding, reading books, solving problems in Android development, and now I feel that I've lost my passion. I feel that mobile development is disgusting. I'm trying to start with Machine Learning, JavaSript frontend development, Python, Java and Spring and everywhere I realise that I have to learn a lot to get a job. I see a lot of ways, but I really don't know what way to choose. I'm lost. I want to die.

Does any of you have the compulsion to micro-optimize every bit of code that you write? How do you deal with it?

I'm not just talking about algorithmic optimizations, but the real nitty gritty stuff. I'm talking about using bit fiddling to avoid if statements where speculative processors might make mispredictions. Anything that might make a program compile to fewer machine instructions or avoid extra stack frame overhead.

This all started a year ago when I took a systems programming course at my university, and started learning C and C++. But I find myself doing this in the wrong places. Who cares if this trivial program that I wrote runs in 1.2 or 0.6 seconds? My future employers won't care if my code is 10% more efficient when it takes four times as long to write.

It's gotten to the point that I can't bring myself to use languages like Python because I don't know how it's implemented under the hood and can't predict how the different ways I could write a function will affect performance. How do I bring myself to trust that the compilers (or interpreters) and the programmers that wrote them will be sufficiently optimal, and just move on? 😩

After rejoining, this place really does seem a bit deserted. So ill try to bring some controversy to this place.

AI, a hype? Machine learning wearing a mask? Pattern recognition on steroids?

What do y'all think? In my opinion its an awesome technology that has many practical applications but it is far from what they try to tell us it is. Its awesome, yes. But under the hood still mostly pattern recognition, classification etc. LLMs seem a bit more complex but still the same thing.

Sure, it's easy to write a program that does a given task a lot better than a human, however its limited to doing exactly that.. So is a calculator.
What I think of then hearing AI is what is now known as general intelligence but just a question of time until they come up with something that can do more than AI and call that general intelligence and actual general intelligence will be called something else.. You get me?

Being a university student who is about to complete his first year, is being a google certified mobile web specialist worth it?? ( More about my background : I have been into front end developement for around 4 months and this has been my first exposure to " production level coding ". I have been improving my JS skills and am currently learning Vue. I have a fair understanding of backend and am trying to build a full stack app using express, Vue and sockets . I have an interest in algorithms , dsa and machine learning although I an not able to devote my full time on it but hopefully would be able to do it in 2 to 3 months. I also have an interest in Linux and all. ). Please suggest something . Thanks in advance.
PS : I know my interests are very random , but I am just exploring my options and being a freshman , I am confused A lot . So trying to figure out something that will help me in future too

Guys, this is not a rant. But I need a career advice. I don’t have a BD in CS, but I studied by myself and took some other classes and was working in the field for more than an year now after graduating from university. I do full stack developing with javascript and sometimes java at a startup now.

My goal was to eventually get to grad school in CS. I found some programs what accept students from non CS back grounds too. I can’t do BD again it will take too long. And I’m old ! lol

If any of you had similar experiences, or know some good programs would you let me know? Should I prepare portfolio or should I accomplish something great in order to get accepted? Or should I just try applying first? I’m focusing more on east coast to choose schools from but open to anything for now.

It’s quite scary to really start working on this since I already have a job and there are so much information regarding grad school, I get overwhelmed. Though it’s something i need to overcome. It would be really helpful for me if you could share your two cents.

I love what I do now, and really hope that I get to study further and explore in depth. Also I’m interested in AI or machine learning. Also if you know good source for reading recently published papers on CS let me know!

Thanks for reading! :)

I wanna cool robot sidekick,
The more irritable the better, like bender from futurama or K2 from rogue one. (Even murderous maniac of a an ai like hal9000 and skynet is fine)

The machine learning technologies aren't just there yet though, they can be irritable but not because of their smart ass answers just the opposite really.

I will need a team with 100+ people that are experts in neurology AND machine learning. Also 10 years.. we will get there !

Machine learning becoming easier to use and more accessable. I know it's been around a while it's just getting way easier to use with out having to get too nitty gritty in things. I really like the idea off assisting human jobs with automation when possible if it's not practical to completely automate them. That's specifically what I'd one day love to work on.

Have any of you moved from Web application development to more deep and complex stuff? I mean without finding it boring. I just moved to data and analytics at my job. And in a few months we will be getting into AI and machine learning. I just don't know if I'm going to find it boring or not. I really enjoy and still love web development.

Dell Summer Internship Experience 

Firstly,to be a part of this process it is important to clear the exam conducted by college and according to me it wasn't something which can't be easily achieved so to prepare of this exam stick to basics of all subjects which have been taught so far till semester majorily data structures,data base,Java,C, operating system were asked.Basics of all following subjects should be clear which also going to help during internship.

I myself prepared for the test from geeksforgeek.I tried to gain as much as basic knowledge of subjects I can.And after selecting from test you have you go through hackathon on that personally I think one should be prepared with latest demanding skills.Mostly all the hackathon topics were in and around Machine Learning,Block chain,Web development,Databases.So typically should be aware of all these technologies and how this can be used to enhance in project.

During hackathon days it is important to be interactive,it  is good to clear doubts or explain your idea and how innovative you project is and how different it can be and further keep in mind how your project can be industrial utilized.Try to make your project more in aspect of how industry going to adapt this or how this problem's solution is perfect in every terms for a company.And majorily at last it comes down to how to present your project infront of your panel.

I think keep that session as much as interactive you can,try to answer their queries,and most importantly know your part of the project very well on theoretical as well as on code level. At last you have to go through a HR interview in which firstly you have to be prepare with a nice resume in which you to include all your achievement's,projects and most importantly keep it short and simple and include only those things which you are completely aware of.For interview first try to know and learn about company, it's goals,in what field it is presently working and during interview there is nothing to worry about you just have to talk like you are talking with a normal person,express all your views ,try to speak out.

Confidence is one important thing for this interview.So this was conclusion of my experience from hackathon hiring process from Dell.

Anyone ever tried to fuck around with dynamic programming in machine learning?
My question is more towards rounding numbers.
Any papers on the impact of learning rate or precision that you guys know of?

I have one question to everyone:

I am basically a full stack developer who works with cloud technologies for platform development. For past 5-6 months I am working on product which uses machine learning algorithms to generate metadata from video.

One of the algorithm uses tensorflow to predict locale from an image. It takes an image of size ~500 kb and takes around 15 sec to predict the 5 possible locale from a pre-trained model. Now when I send more than 100 r ki requests to the code concurrently, it stops working and tensor flow throws some error. I am using a 32 core vcpu with 120 GB ram. When I ask the decision scientists from my team they say that the processing is high. A lot of calculation is happening behind the scene. It requires GPU.

As far as I understand, GPU make sense while training but while prediction or testing I do not think we will need such heavy infra. Please help me understand if I am wrong.

PS : all the decision scientists in the team basically dumb fucks, and they always have one answer use GPU.

One day I decided I wanted to build robots.
And not kidding the reason I wanted to build them was because I wanted someone interesting to talk to and stil not kidding I even fantasized about a robot girlfriend... Lame I know I think I was a lonely little guy back then, though even after 7 years or so it doesn't feel as though it's that long ago. Maybe because things didn't change that much. Which is worrying but it's not the topic so I will pass on that future-past worries bullcrapper. After learning how robots worked and what made them function so things gradually led up to me being more interested in machine learning applications and software. I learned Arduino at first, I think I still have some messy circuits and old arduinos around. I only finished one robot though and it couldn't even support it's own weight. The servo motors were taking too many amps that heated up the little arduino even with a fan attached. Provably I should have made use of mechanics for robots books and calculated things first. But even though it couldn't walk properly I still felt success and I loved it like my own kid (me taking it apart was questionable but believe me). After that I focused more on writing code than using my hands to make things which was a pain in the ass if I might add.
After learning arduino and making that failed project of mine. I then picked up C++ wrote hello world program usual things a starter would do. It was the language I wrote my first game which I finished and this time it worked. But I never released it which was partly because I didn't want to spend a hundred bucks on a license for the engine and I also knew that it was a shit game. If I were to describe; lines in different colors come from the top you need to hit the lines with the same colored columns to break them. The columns changed their height and location on random. The lines sped up and gap between them decreased. Now that I think about it it wasn't half bad. But the code was written in game maker studio's version of C so I have no way to salvage it.
But I learned a lot of things from that project and that was the goal, so I would call it a win. I don't remember but after sometime I switched to python. And I'm glad I did, it's fun to code in which was the main reason I coded in the first place. Fun.
Life happens and time passes,

Now I'm waiting to enter college exams in a few months after hopefully passing them. My goal is to get into computer engineering which will be extremely challenging because it's the highest point department in the university I'm aiming at. But hey if the challenge is great the reward is greater right ? To be honest I'm still not sure about my career path. Too many choices. So I will just let my own road called <millions of similarly random events that are actually caused by deterministic reactions, to affect you and your surroundings leading up to a future which only the Laplace's demon can forsee> guide me. Wish me luck.

So I have a STUPID question about Machine Learning.

And I am being serious when I say this.

I want to get into machine learning but I really don’t want to accidentally create the AI that kills us all.

I’m not trying to boast my abilities or anything I’m not that great but I just

one don’t completely understand how machine learning works?

And two how do I keep it from learning more than I want it to??

I’m not trying to be stupid I’m just trying to understand so I don’t make anything that I regret.

ok I think a lot of my frustrations in rust stemmed from assuming struts are like objects and therefore can contain conceptually similar things in them that in your head would seem like the same "object", and that methods should be derived therefore and such

but in reality in rust struts are for conforming to borrowing rules and it doesn't care about your conceptual organization I guess. if you try to organize things like the structs as objects then you get borrowing issues on some occasions and then I would get stuck trying to figure out how to put a method on a struct when I need to drop borrowing to do some task and whatever

the solution is to throw out your human notions of organization

so I guess it's more bare-bones to how the machine thinks about stuff (well how the borrowing is coded in the language) and doesn't care how a human does (like notions like object orientated design)

this is odd to me in a modern language but at least I've crawled out of my brain damage with enough drug-use now that I can have such epiphanies I guess. I feel so slow. I swear this should've been massively obvious and easy to grasp in like a few days before for me. rip

instead it was 2-3 years of ~5 months of actually deep coding 😒

also I can blame people saying rust can do everything, like that you can do object orientated design in it. they're being dishonest and it's harmful to the learning process if you're acting like that 😩. stop being a cult, you'll literally be more popular

[long confession/question]
So I was asked by a client to make an app similar to prisma(not exactly that but let's say a caricature app) and I knew I have to research a lot.

Now I have been loyal to PHP for over 5 years so I first tried with GD and imagick but the results were not very good, so I thought let's try opencv. I didn’t wanna make any compromises so I didn't go the bridging way, I worked on native python even though I am a newbie in it. I was fairly impressed with the cartoonizing results but others weren't. Soon I got to know that this would take much more than simple filter combinations or matrix manipulations.
I read about prisma and got to know it uses deep neural networks for the same.
Now, in the five years I have learnt almost all the things a run-of-the-mill "Full stack Web Developer" should know.
I have a fair knowledge of PHP, many of its frameworks, many js frameworks(obviously jquery), I have a very good understanding of CSS and its models, I have worked on some cool algos and found solutions to many problems but I haven't gotten to stage where I can implement neural networks/machine learning in my projects.
It just scares me.
___
A little back story: I have been the CTO of a small scale company for about 1.5 years now.
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So all this got me to asking myself should I just step down from the post to a position where I can learn more skills. Managing takes a lot more time where I can't learn a lot. Sure I learnt some other important things but not as much tech knowledge as I would have in a more basic position.

I know not many of you must have read this far, but if you did what do you think I should do? Really depressed at the moment.

Are there any good courses for practical machine learning (that uses an actual language)? I tried out Andrew Ng's course and it seems more theoretical than practical.

Need advice:

So I’m 20 years old. Got a decent job as software engineer with a really good pay and really want to break into machine learning.

Mastered NodeJS (my stack has always had node for the past 5-6 years) and I’m finding it difficult to switch to python for machine learning since things are so engraved in my head in javascript.

Aside from the syntax when I’m watching tutorials or reading books, I see data scientists and mathematicians make design mistakes in their code and it hurts my eyes and triggers my ocd.

I need tips on how to put my mindset in a moldable state so I can judge less and learn more and absorb data. Like you know that philosophy that when u get old your brain can’t learn things as fast anymore? I feel like that’s already happening to me rn at the age of 20.

Wow that machine learning algorithms turn my brain in 🍜.
Someone have more simple course on that?

Decided to continue my studies because I really wanted to go into Artificial Intelligence. Even though I've learnt some here and there in Machine Learning, Deep Learning and its various modules of supervised and unsupervised learning but I felt like that I'm not getting anywhere and need some proper guidance. Decided I could take a Masters in this specific field with a lecturer's guidance.

Enter my boss, I've asked for consent if its OK for me to continue my studies. He goes on and on that employees are valuable and that we're at the start of a big project currently (even though I've asked that I'm thinking of taking the next intake in September 2019) and couldn't afford to lose my time to studying A.I. Not only that, he insulted that A.I. is useless in a Fintech company. And instead he wants me to learn about blockchain tech.

Who is the choosing beggar here?

I mean OK, I get it. I've seen mature students who took on part-time studies to get diplomas and degrees and I understand the huge stress in assignments and research. I'm well aware of that and I've done self-paced studies for a long time now. I believe I can handle the pressure and time management in juggling between work, study and life through past experience and observation. How is this any different aside from doing towards a degree?

He even felt threaten that I might leave and get a better and different job after I graduate. Does he think I'm stupid to tell him about my intention if I knew that I'll be getting a better paying with more perks job than what I already have with him? I didn't want to leave my good job as there's loads of things I want to do for the company. But since his attitude towards my education pursuit shows, I think I just might. I don't know. I like the company I'm working for. Just not for him.

I know c++ and python both and I want to choose machine learning as my career field but I don't know which language is more helpful for me and in what portion I need what..
Can anyone please tell me what language should I go with and why. Also tell me the implementation of that particular language in this field...

WSL seems really cool from what i've been toying with it. WSL2 seems like it'll be even better and the integration with docker(another thing i'm toying with) looks interesting. as far as i can find though it's only on windows insider for now, and I don't like having telemetry on my main machine.

So i spent a good chuck of my day just setting up Hyper-v, learning about nested virtualization (so docker will work), setting up a win10pro vm, and i'm now in the process of setting this up to be a virtualized dev machine (not gonna be a one use only system cause i spent way too long on this shit) and setting up docker and wsl

I don't know much about docker or WSL beyond just some random stuff i've learned to toy with to simplify some things i do. but maybe this will give me a cool way to actively learn more about them and maybe use them as more than just boredom toys

I want to add Python programmers engineer , SQL Server engineer, machine learning engineer on my social media like Instagram , Snapchat , LinkedIn , WhatsApp etc . To know about better understanding of these languages and their concepts and explore more in engineering field . Plz comments your I'd and be my mentor .
Your friend ,
Degel(Rahul Vishwas)