Interviewing a Data Scientist

Buzzword dictionary to deal with annoying clients:

AI—regression
Big data—data
Blockchain—database
Algorithm—automated decision-making
Cloud—Internet
Crypto—cryptocurrency
Dark web—Onion service
Data science—statistics done by nonstatisticians
Disruption—competition
Viral—popular
IoT—malware-ready device

Was originally hired for 3 months.

Just finished the project 2 weeks ago, after 1.5 years.

I fucking hate data science now.

"I am still cleaning the data"
- A data scientist's equivalent of 'It's compiling'

Recipe for a Great Programmer:

Ingredients:
-Books for a computer science curriculum from a top university
-Computer
-Headphones
-Internet
-Stress ball
-Pillow
-Lighter fluid
-Food

Directions:

1. Cover computer science books with lighter fluid
2. Light books on fire
3. Use flames to cook an energy-rich meal for the thousands of hours ahead
4. Pick an IDE
5. Choose a project beyond current capabilities. Good ways to push boundaries:
- Unfamiliar domain (e.g. large scale data processing, UI programming, high performance computing, games)
- Exotic programming language
- Larger in scope than any project before
6. Shut up about your IDE
7. Attempt to build
8. Stop procrastinating on Hacker News
9. Re-attempt to build
10. Squeeze stress ball and scream into pillow as necessary to keep sanity
When stuck:
- Paste stack traces into Google
- Find appropriate mailing list to get guidance
- Realize that real learning happens when you are stuck, uncomfortable, and/or frustrated
- Seek out books, classes, or other resources AFTER you have a good understanding of your deficiencies
11. Repeat #4 to #10 for at least 10 years
12. Results guaranteed! (to the same extent static types guarantee bug-free programs)

source: nathanmarz.com

Facebook: "Our facial recognition automatically tags people in pictures."

Tesla: "Our deep learning algorithm drives cars by itself."

Andrew Ng: "I predict patients' likelihood of dying with 99% accuracy."

Google: "You know one of our algorithms is going to pass the Turing test very soon."

Wall Street: "We use satellite images to predict stock prices based how filled car parks of specific stores are."

The remaining majority of data sciencists: "We overfit linear models."

A tool I built for my past company just got nominated for a European Data Science and AI award!!!

I'm over the moon that something I built is up for such an award. Be early next month before winners are announced. Oh and given I don't work there anymore, how I was told about it is a REALLY funny story .... I wasn't.

Saw a Linkedin post from my ex-manager congratulating the company and the org for great work done. He/They just forgot to mention the fact that me and another ex-employee did everything, left it practically finished and completely changed the direction of the project within the first month as their plans made no sense.

fuckers.

Professor essentially doing a dance to show data visualisation:
“Hey pay attention! I’m trading my dignity for your education”

Look what I found!
Even my L3 cache is bigger than this!

“Those were the days😂”

Presenting my research on fraud detection with Machine Learning

!rant
Yesterday i updated my LinkedIn title to Data scientist.
Today morning i got 3 phone calls for job offers.

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!

Dropped my youngest off at the childminder today and her husband asked me what I'm doing for a job now
.. Explained its security and data science... His reply was to ask if I can setup a printer....

Guidance counselor at school: so what field do you want to go into?

Me: computer science

GC: what does that entail?

Me: programming

GC: that's like super repetitive, right? You're a smart kid don't do that

In my head: no you mf dingle-dong. That's the job that will take your job away from you in the next 5 years

Ffs, why do people think coding and entering data into Excel are the same things?

I just released a tiny game for iPhone!

It's basically an attempt to mix 'Heroes of Might & Magic' and mtg.

In the screenshot my terminal says 'helloworld.cpp'. That's right, this is my first c++ program and I don't care how crappy you think this game is, I'm super proud of myself!

I've always worked in data science where managers assume I know how to code because there's text on my screen and I can query and wrangle data, but I actually didn't know what a class was until like 3 years into my job.

Making this game was my attempt to really evolve myself away from just statistics / data transforms into actual programming. It took me forever but I'm really happy I did it

It was brutal at first using C++ instead of R/Python that data science people usually use, but now I start to wonder why it isn't more popular. Everything is so insanely fast. You really get a better idea of what your computer is actually doing instead of just standing on engineers' shoulders. It's great.

After the game was 90% finished (LOL) I started using Swift and Spritekit to get the visuals on the screen and working on iPhone. That was less fun. I didn't understand how to use xCode at all or how to keep writing tests, so I stopped doing TDD because I was '90% done anyway' and 'surely I'll figure out how to do basic debugging'. I'll know better next time...

I've dreamed of learning business intelligence and handling big data.

So I went to an university info event today for "MAS Data Science".

Everything's sounded great. Finding insights out of complex datasets, check! Great possibilities and salery.

Yay! 😀

Only after an hour they've explained that the main focus of this course is on leading a library, museum or an archive. 😟 huh why? WTF?

Turns out, they've relabled their librarian education course to Data science for getting peoples attention.

Hey you cocksuckers! I want my 2 hours of wasted life time back!
Fuck this "english title whitewashing"

A beautiful collage....

M - Me
F - Family member

F: So you study computer science... Could you recover my Gmail login data? I don't remember my email address, password or security question. (7th request to me like that from the same person, they don't bother to write down the recovered pw)
M: I can't do it if I don't know any of the above
F: Wow, I thought you're a good student... Could you at least create a new account for me?
M: But you won't even remember the new... [gets interrupted]
F: So, are you going to talk trash or get to work? You would have already been 50% done

PLEASE I'M SO TIRED OF IT. HOW DO I DEAL WITH THESE OTHER THAN TELLING THEM WHAT I THINK ABOUT THEM. I SEEK HELP

My neighbor(He is 14 I think) pitched this to me and wanted advice since he was going try to participate in the Google science fair.

Him:"A robot that gives you medical advice. You just tell it your symptoms and voila! You've got your diagnosis. No doctor required."

Me: "How are you going to decide what disease the user has?"

Him:" I'm just going to write an if-else ladder statement. I've already got some of the data from this site called WebMD. It's amazing."

Me: "Go with something simple. What you're suggesting won't work out."

He told me I didn't have "Vision".
His ditched his project last week.

So today I made a mock exam of data science.

!rant

We just did a massive update to our prod db environment that would implicate damn near all system in our servers....on a friday.

Luckily for us, our DB is a badass rockstar mfking hero that was planning this shit for a little over a year with the assistance of yours truly as backup following the man's lead...and even then I didn't do SHIT

My boy did great, tested everything and the switch was effortless, fast (considering that it went on during working hours) and painless.

I salute my mfking dude, if i make my own company I am stealing this mfker. Homie speaks in SQL, homie was prolly there when SQL was invented and was already speaking in sql before shit was even set in spec, homie can take a glance at a huge db and already cast his opinion before looking at the design and architecture, homie was Data Science before data science was a thing.

Homie is my man crush on the number one spot putting mfking henry cavill on second place.

Homie wakes up and pisses greatness.

Homie is the man. Hope yall have the same mfking homie as I do

So my first job is also my current one. I am a computer science student and for my course we had to do a project for an actual client. The client was a consultancy company and after working my ass off, their software development partner decided to hire me and a classmate.

The company is pretty small (we are now with the 6 of us) and the general attitude is very nice. I've only been working there for a few weeks and I feel very welcome. The work isn't too hard (mainly web development with geographic features/data).
In rough lines the stack always consists of a Java Rest API and an Angular frontend that retrieved the data from the API.
So far I have learned a ton and I am really happy that I have this opportunity. Lunch is provided and we always eat together, we crack jokes, have fun, play games in the break. Coffee machine next to my desk. I'd love to work here all my life :d

Since I'm still in school I can't go to the office every day. Instead I am at the office every Monday and on other days I try to work from school or home.

$50,000+ Computer Science fucking diploma, yet here I am on a Sunday evening doing data entry coz there is no one else to do it!

"we use machine learning to ..."
Ffs you're interviewing a developer, not pitching to a investor. We know how much machine learning you use.

I attended a data science meetup recently. There were many suits walking around the corridors because of some startup night taking place at the same time.

After some time a guy appeared infront of me, telling me he was afraid at first that this was a meetup for suits only. Until he saw all the dev and rock stickers on my notebook. He was reliefed that there was some nerd at least.

He asked what I was doing so I told him about my startup about optimization of heat generation plants jada jada. I asked him back.

He replied, "Well, I'm also part of some small startup. Among the things we develop processors and stuff. It's called Intel."

Well dude, that was nicely played. I had a lot of fun that evening.

**Me completing data science courses**
ACCURATE.

My dream was shattered!!

I joined a new company. I graduated last 2 months before and joined as data analyst.
So I was dreaming to work on some awesome research projects and all, but it was just another dream...people here don't work on any sort of data analytics instead the data science team uses regex and all to extract things and say they are building models.
Ahh...wtf!!!
Many co-workers are good and help me, but the boss. He left all the annoying works to me and the release is in next month...
"BRUH I JUST JOINED YOUR COMPANY!!!"
Then after some days he gave me more task, when he found that one task was super easy(i mean it was just to extract things using bs4 and selenium, hardly will take an hour) to do then he took that himself and in the next meeting said he did that work and it was super difficult!!!
Data science here to senior members is just for loop!! I dont even know why I joined this firm
Ahhh!!! I want to scream!!!

Trying to get more hardware from IT for data science be like...

Hey, guys!

I'm new here and I want to introduce myself and meet you too.

My name is Mariana, I'm 21 years old and I live in Brasilia, capital of Brazil.

I'm a beginer in the world of development and I joined on this community to know more about this world. I am currently studying js, react and react native, but I am passionate about database, in the future I want to work with data science.

And you? Feel free to introduce yourself too! :)

What sort of fucking asshole decided to name it "data science"? We already have a "science of studying data", it's called Statistics...

Just because you can learn HTML in a day doesn’t mean that you don’t need a degree.

Did you know that your browser, HTML, CSS, Javascript, and even your operating system use linked lists, binary trees, hash tables, and other so-called “useless” data structures?

It’s important to understand the roots and fundamentals of computer science even if you won’t use that knowledge day to day.

It changes your perspective on programming once you learn what actually goes on under the hood, and makes you think twice about the impact of what you write.

It’s relatively easy to get a programming job without a degree nowadays, but it often leads to web developers claiming that degrees aren’t important to their web apps.

There is much more than just the web to computer science, and that’s something to always keep in mind.

"His graphs are bigger than mine."

🤐

Hope there is no Data Scientist here...

Most kids just want to code. So they see "Computer Science" and think "How to be a hacker in 6 weeks". Then they face some super simple algebra and freak out, eventually flunking out with the excuse that "uni only presents overtly theoretical shit nobody ever uses in real life".

They could hardly be more wrong, of course. Ignore calculus and complexity theory and you will max out on efficiency soon enough. Skip operating systems, compilers and language theory and you can only ever aspire to be a script kiddie.
You can't become a "data scientist" without statistics. And you can never grow to be even a mediocre one without solid basic research and physics training.

Hack, I've optimized literal millions of dollars out of cloud expenses by choosing the best processors for my stack, and weeks later got myself schooled (on devRant, of all places!) over my ignorance of their inner workings. And I have a MSc degree. Learning never stops.

So, to improve CS experience in uni? Tear down students expectations, and boil out the "I just wanna code!" kiddies to boot camps. Some of them will be back to learn the science. The rest will peak at age 33.

Literally anything but work with computers, I think. They ask my brother to fix anything technical in the house and ignore it when he fails. They haven't been able to watch TV in six months. When I suggest that my (well-intentioned but mostly nonverbal) sibling probably shouldn't go into development, they tell me I don't know my own job. I suspect they're convinced I do graphic design.

I write C++ applications that run physical simulations and sometimes train AI models for pattern recognition and highlighting unusual incoming files.

They suggested I go to an undergrad program for data science. I already *do* data science for money and I already have an undergrad degree. 🙄

WHY DO PEOPLE USE STRINGS ON THEIR BINARY CLASSIFICATION DATA LIKE IS IT HARD TO USE 0 AND 1?!?!

Agreed? 🧐

U can forget wearing your pants but never these 3...

TLDR Question:
When do you consider yourself an expert at a language?

More details: there is a really cool Data Science internship opening up near me that I want so badly it physically hurts me, but it asks for expert level knowledge of python, Java, or R.

I’ve only been studying R and Java for like 3 months, and Python for about 8 months, so I’m obviously no expert. When exactly does someone reach that threshold, though? When did you realize you were an expert at a language?

Two weeks ago, I chose my modules for my Master in Data Science. This morning, I received an e-mail to tell me it was a bug, I was not accepted.
.
So what's now
.
I guess I will kill myself

data science is just a sexy word for statistics.

1% programming skills
99% practically all science thats not computer science

Code never lies
Comments sometimes do

Nah!
Code lies too, especially when you train a neural network 😂😂

zero motivation for anything, i just want sit outside in the sun at the lake with ice cream and not in front of a screen. And not being bothered by the new vacum cleaner loud deep learning rig of the data science department in this open floor office.
I fucking forgot my noise cancling headphones. FML

Should I actually look into getting a dev job..?

*I have a high school diploma (graduated three years early)
*College dropout (3-4 months, Computer Science - Personal Reasons)
*No prior work experience.
*Good textural communication skills, poor verbal communication skills.
*Currentally unemployed. (NEET :P)

*I have extensive personal experience with Java, and Python. Some Lua. Knowledge of data generation, parsing, Linux, Windows, Terminal(cmd & bash), & Encryption(Ciphers).
*Math, but very little algebra/geometry (though, could easily improve these).
*Work best under preasure.

Remote only.

Think anyone would hire me..?

The joy of a complete trained model.
Onto the next task. Use the model to automatically infer handwritten figures on a bankers check/cheque.

101, How to get approval for your projects...
source: LinkedIn

When you forget to normalize or standardize your data.

Cousins came over...

Me: just compiling some python code, opens up jupyter notebook to take a look at some data science code
Little Sis: *looks at jupnb dump on cmd*
Whoa are you Hacking?
Me: yeah. I got bored of whole Hacking command typing thing so I opened up my hacker console.
*print("hello world")*
Sis:wow!
Me: you know what, typing is too tiresome, I'll connect to it with my mind
*alt-tab*
*cmatrix -b*
*sits in yoga pose*
Little Sis: Screams at the top of her lungs and runs to aunt
"DAVE IS HACKING MATRIX"

I created a curriculum to homeschool myself way up for a MSc in AI/ML/Data Engineer for Application in Health, Automobiles, Robotics and Business Intelligence. If you are interested in joining me on this 1.5yrs trip, let me knw so I can invite you to the slack channel. University education is expensive..can't afford that now. So this would help but no certificate included.

A girl takes less time in getting ready as compared to windows 10😂😂😂
#WeekendHumour
#myOriginaldontCopy😏

in the past 48 hours my partner must have asked me 50 times to create an "AI" that can get the data we need off of wikipedia.

Background: I am in AP Computer Science AB but I have been programming long enough that this class is a joke. We were assigned to partners with the task of creating a search engine that finds informations on wikipedia("which is dumb because thats what the search tool is for") so I created a Java Web-Scraping program in probably 30 minutes and showed my partner. He told me I am completely wrong because it would be "cool" to incorporate machine learning into the assignment.

Do I even tell his what machine learning is or should I just let his figure it out?

Anyone else taking Harvard's CS50 via edX? It's so awesome! You get a better understanding of Computer Science and stuff. I'm loving C! It feels so close to communicating with the machine. Memory allocation fascinates me, too. Is this why it's fast? If you feel like you're lacking with the CS fundamentals although you can build apps or websites already, I recommend this. This is better than my whole years in college!

This is how U became a Data Scientist 😆

So according to Pfizer, ~39,000 people received a second dose of vaccine/placebo. So about 20,000 got the placebo, and out of that group only 85 got infected in the span of 3.5 months, during the second wave. That's 0.425%.
So they either:
* Proved Covid is not infectious
* Manipulated the shit out of their data
How that fuck is this considered valid analysis?!
If I tried to publish a paper based on such unreliable, statistically meaningless data, I would be rejected without a blink.

The guy who became my manager just pushes to the prod branch.

On a repo where another team clearly set up development and production branches.

This guy has been pushing code like crazy and I always wanted to take my time setting things up properly in our team: TDD, CI/CD, etc.

Because he pushed so much he became my manager and I was seen as unproductive.

Data Science and software development best practices just dont coexist it seems.

Yeah yeah, it's up to me to start introducing good practices, but atm "getting it done" takes priority over the real based shit.

Yesterday I met my cousins who are old enough to have kids. It was a good talk with them bringing back the old memories. One of my cousins has a barely 5 year old kid. I tried to talk to her and the conversation went like this:

Me: “hey there! Hi, how are you?”

She: “Good. What do you do?”

Me: “I am a computer science engineer. What do you wanna be when you grow up?”

She: “A scientist.”

Me: **thinking calmly, “Oh, what kind of scientist?”

She: “A Data Scientist.”

Me: **Two seconds of silence and decides to leave...

Visual Studio (Code)

-Cross-Platform App Development
-Cloud Integration
-Extensions/Packages
-Lightweight (Installer VS2017)
-Many of Langs (C#, js, Python, F#,...)
-Data Science Tools built in
-...

Bid your price 🔨

Programmer’s life cycle:
- Nothing can stop me today
- A bug huh? let's squash
- I can’t fix this
- Confidence crisis
- Questions career
- Questions life
- Oh it was a typo
- Nothing can stop me today

I'm that person that makes shit inefficient code, hello everyone. I'm just now learning algorithms and data structures after years of employment.

It is my hope to one day atone and be forgiven for my crimes against computer science.

Switching to macOS was an entry to paradise.

I go to Windows only to play Call of Duty. It’s crap and always will be.

P.S no comments on Linux.

This is just straight up a joke. Head of data science has had us implementing something based on a paper.

I raised some "concerns" about it a while ago. Found out today they'd not even read the paper. We're pretty sure what we've been asked to work on doesn't solve the problem it's meant to solve...

"What is Data Science?" The title of the first slide of way too many data science talks.

Just changed my wallpaper to be the Tensorflow logo and added 'background in data science' to my CV.

We bother only about errors not warning

Visual Basic at high-school, pascal and C and Java at University. VBA for macros on a job. html+css+js learnt o er a weekend to pass the screening for a new job, then ruby and php on that job to build internal tools. Now I am into python for data science. It has been fun.

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

Worked as a student in a big company. Just doing data entry and checking product data. It was a nice part time job at the same time with computer science study. After a year I asked for something else and switched to the Android Team. I said I could do a little bit of Java and wrote for another half year Unit Tests. That was the point where I really learned coding and got experienced. Would never learned so much in my study because I was lazy. Now I can call me a Android Developer. Still love the company for giving me this opportunity.

Me to university: You taught us C++, java, DS Algo and PHP only right?

University: Yes

Me: So our college project must be around these only?

University: Yes... But No, here are your only options for our college project

1. MEAN/MERN Stack Website
2. Machine Learning
3. Data Science
4. IOT
5. Android App

Me: WTF?

Apply for a data engineer role.
Get invited for a data science interview.
HR says they're building AI and I were to supervise another person writing its algorithm.

It's a media company.
*Risitas intensifies*

The model developer may have got it

Someone asked me about Ruby vs Python.

The flashbacks regarding the python vs ruby wars started to kick in man.

I always liked Ruby faaaaar more than Python. And find Rails to be a far superior alternative to Django as the web framework champion from each side and Sinatra far more enjoyable than flask as the micro framewor champion on each side goes.

But this guy is very math oriented and likes the idea of data science for which Ruby has a disadvantage in terms of available ecosystems.

You can't take my blocks and dsls from me tho. I will fight for them.

So I finally got a job where I was an intern as a Data Scientist.
PS : I am a non-computer science background guy, who made it through.

so I left uni after my PhD and joined a start up where the boss is a Cambridge grad who does coding and is like 50 years old (he never told us the true value), the CTO is very talented and another dev who quickly became my best friend and me doing data science. the 4 of us worked together like friends and the efficiency was fantastic, there's no bureaucracy bullshit or shit boss talks. We built the whole thing from scratch (okay I admit they did most of the building) and to this day, we work just has we have been.

"Non-devs never call Steven Spielberg to have their TVs fixed."
But sure they MUST call a dev to update their Android, iPhone, Windows, installation of Anti-virus, data recovery, malware removal, to shortlist 20 laptops from market, ask for what printer to buy, why is there a weird animation in Android sometimes, come borrow my WiFi, have their phones and computers fixed, RIP old audio CDs (yes!), fix Bluray, fix anything electronic, repair their bike, teach them science, politics...
This While True loop never escape.

Corporation.
Meeting with middle level managers.
Me - data scientist, saying data science stuff, like what accuracy we have and what problems with performance we managed to solved.
Manager 1: Ok, but is this scrum?
Manager 2: No they're using kanban.
Manager 3: That's no good. We should be using DevOps, can we make it DevOps?

So yea, another great meeting I guess..

Waking up and guess the first item on my feed?
IBM research just released Snap ML framework that's supposedly 47x faster than Tensorflow. Now, i like advancements but fuck i just finished developing my Tensorflow model, and i don't want to rewrite this stuff again!

The everything is Data science craze trend.

Honestly it's not even sustainable with every kid and their grandmother wanting to be data scientists because it's a 'passion' and a 'dream job' and all of that click bait stuff.

It's just become ridiculous at this point and I doubt we'll even have the long awaited 'breakthroughs' people have been talking about for so long.

Also I have a strong feeling everyone thinks it's their 'passion' because it tops the lists of highest paid jobs out there and everyone thinks with 3 months of training they're a fully fledged data scientist because some Python or R package implements all the algorithms he could ever think of using.

Add to that the fact that most advertised data science jobs are actually data engineering where you maintain a date store and that's it.

Agree or disagree that's my piece and if you can convince me otherwise I'll be surprised because I've been subscribed to this idea for so long that it lost me some real good opportunities because I thought it was just what I was meant to be doing which turned to be false after I thought about it. There's a million other jobs that are more impactful and with pursuing.

Merry 2018 in advance.

If it aint a secret, comment w/ your new years resolution so other lazy fucks can get motivated.

Mine: a 3d game (godot), releasing my data science java libraries, building some kind of robot

Redeveet..

You know. I think people trashing chatgpt detracts from the fact that if it is actually functioning as stated it's still a goddamm miracle of science!

I mean are we all really that jaded ?

You can type a plain English request in and a COMPUTER PROGRAM sends you a Novel response that may reflect the bias of its dataset and the bias of people trying to keep "secrets" but otherwise it sends a response formulated from extensive data.

That's a breakthrough

Quick acting like an alpha that was frozen years ago apparently is the RTM!

A fellow <insert some data science title here> giving me more acknowledgement than all of the old guys running the show and, erm, "leading"?

Fucker left me behind, good for him.

Over the last year, I’ve only started learning computer science at uni, never done it before.

I’ve done units in:
- Alg. and programming fundamentals in python
- Intro to comp sci
- alg. and data structures
- theory of computation

Guess the point of this is, “why do people code, what aspirations do you all have?”
Cause rn, I’m all about “I have no idea what I’m doing, coding just seemed cool and I wanted to try it out.” Don’t know where to go

Someone inspire me???
Here is a legit reason for you to brag about what you do and what you’re going to do 😉

INTERVIEW. It tells everything about the company. I recently applied for a "big" company for the position of ML Engineer. The Job description was like "someone with good knowledge of visual recognition, deep learning, advanced ML stuff, etc." I thought great, I might be a good fit. A guy called me the next day. Introduced himself as a manager of the Data Science team with 8+ years of experience. Started the talk saying "it is just an informal intro". But things escalated very quickly. Started shooting Data Science questions. He was asking questions in a very bookish way. Tells me to recite formulas (like big formulas). When I explained to him a concept, he was not understanding anything. Wanted a very bookish answer. I quickly realized I know more about ML stuff than him (not a big deal) and he is arrogant as fuck (not accepting my answers). Plus, he has no knowledge about Deep Learning. At the very end, he tells me "man, you need to clear up your fundamentals". WTH??? My fundamentals. Okay, I am not Einstein or Hinton, but I know I was answering things correctly. I have read books and research papers and blogs and all. When I don't know about things, I tell straight away. I don't cook answers. So the "interview" ended. I searched that man on LinkedIn. Got to know he teaches college students Data Science and ML. For a fee of 50,000 INR. It's a big amount!! Considering the things he teaches. You can find the same stuff (with far higher quality) free of cost (on Coursera, Udacity, YouTube, free books, what not). He is a cheater. He is making fool of college students. That is why I sometimes hate "experience". 8+ years of exp and he is such an a**hole!! BTW, I thanked God for saving me from that company. Can't imagine such an arrogant boss.

TLDR: Be vigilant during interviews. It tells a lot about the company.

Data Scientists/Researchers

Stop building libraries.
You can't build libraries.
You're not software engineers.

Write your script as plainly as possible.

Why?

Cus for every fucking paper that has code associated with it, unless it's from Meta or Google, I'm having to edit to make shit work.

Stop over-engineering shit.

Write your model and fuck off.

Data scientist and related devs, how do you handle large datasets?
I was given a .txt file containing +1M edges of a directed graph. I tried to analyze it with networkx, but my computer killed the process as it was eating too much CPU/memory.
I would be grateful for any advice!

While scraping web sources to build datasets, has legality been ever a concern?

Is it a standard practice for checking whether a site prohibits scraping?

Finally finished my application to do Data Science. Fingers crossed I get it!

Building a Deep Learning environment on Windows is such pain in the ass.

C might be a pain to write, but holy cow does it run circles around python from a performance perspective. Easy to forget in fields like data science, where python is the default

Data Science in Python is mind-blasting.

Being in Data Science and Mobile Development taught me :
1.Always be curious
2.Never stop learning
3.Never give up
4.Don't be afraid of Experimenting new Technologies
5.Don't always take ,Give More ,Share More!!

Do Share What your Domain taught you in the Comments 😀

Riddle me this

Client wants solution based on open source software.

Any additional software that I write (let's say, an offline store plugin for Feast feature store) to add missing functionality has to be closed source.

Fuck you. Intellectual property my ass. You and me wouldn't even have projects if it werent for OSS.

Good luck maintaining the plugin after I am gone.

I'm doing a lot of work and will have close to nothing to show to future employers.

(BTW, if it were for the old Microsoft model of code source, I would have never become a programmer of any sort. God bless OSS)

Girl (trying to turn things on): people from my country are great in bed.
Guy: what data points do you have ?
*Girl walks out of the room*

I am so fucking happy I spent time and money getting a college degree in computer science so I can write python scripts to label data. Seriously fuck my lead

#1 Sharing co-working space with my wife.

#2 my home office! (I transitioned from music industry work into data science over the last few years)

What IDE do you use for python programming?

Well, my country has a Degree called Bsc.CSIT which literally means Bachelors of Science Computer Science and Information Technology. I completed that degree and was employed right after I completed my degree. I have worked in two offices and no one cares what degree I have.

So I think Degree is not that necessary here in Nepal as long as you can get the job done.

Now I am about to pursue a Big Data related degree hope that is not as worthless as my current degree.

Trying to switch my job. Applied for a well known company. Gave an interview today. I don't fucking get the obsession of these developer recruiters so fixated on data structures and algorithms. I know it's a massive part of computer science but guess there is no fucking room left to innovate in there. There are legitimate researcher teams working for implementation of these barebones inside system foundations. No general software developer gives a fuck about this piece of shit discipline of study. You wanna know why they propagate this as the panacea to test people because it's fucking easy. Give a project to somebody as interview procedure, it'll take time to bring out an interesting problem and an interesting solution to that. Sorry to say but all these data structure enthusiasts are nothing better than board game enthusiasts.

Also why can't you refer existing solutions to create your solution. I've seen some good problems which actually require you to think. But again those are heavy and can't be tested so you're left with reversing a fucking linked list with O(1) auxillary space. Fuck me ig.

Moreover, what the fuck is wrong with the moral policing internet crowd. Its so sad. I've hardly seen anybody rant about this piece of shit system put in place to push the absolute dead-end nutcases up the ladder. Every other search for it returns a Quora link with some Indian guy complaining about his interviews and in the comments you have the same scholars sitting in their data structure throne imparting knowledge about how data structure holds the fabric of reality together.

I don't hate data structures and algorithms as a subject. It is cool and quite extensive but once you try to make that as a metric of all the knowledge in the world, you've lost my drift. Maybe I'm just angry with the state of things. Maybe I'm just angry with token Quora crowd.

Last week I got told by an incoming CTO, a week old to the organisation, that I'm good for nothing and unable to produce any work. He told me that he'll replace me and put me in a team where I'm more resourceful as I have been consistently underperforming. (He doesn't understand data science yet fyi) Then, he informed he's hiring 5 new teams members.

Me (junior data scientist) being really passionate about work was shook to hear this. So much so that it took me a week to even recover from it. I have considered counselling sessions too.

Week later, 5 new team members decide to flip his offer and not join. Another existing senior member decides to leave as well. Meanwhile, major issues in existing systems emerge and only I could solve the same. Still haven't heard back any from him though.

Is this the industry standard though ? Is this how CTOs normally function ? Throwing shit at people without knowing their value or valuing their efforts ? Especially with junior developers. It's only been 2 years in this profession and I've not met more than 3 genuine and helpful people. Maybe it's just my organization.

I recently tried to apply the same data analytics rationale that I use at work to my personal life. This is not a rant, it is more like an data storytelling of an actual use case I would like some input on.

I set a goal - gotta thin up a bit and calm down my ticker - and got a (almost unreasonably expensive) field expert consultant to yell at me about it for a couple hours.

I unravel the metrics - there is like a million weight-related KPIs and most say nothing at all. I have never seen an non-infrastructure measurable subject that could not be resumed to 2-5 performance metrics. I got overall weight, how well my nine-years-old business suit fits me, heart rate, and day-after relative muscle pain (it will make sense soon).

Then its data-pipeline time. I bought a cheap weight scale and smartwatch, and every morning I input the data in an app. Yes, I try to put on the suit every morning. It still does not fit.

After establishing a baseline, I tried to fit different approaches. Doing equipment-free exercises, going to the gym, dieting. None was actually feasible in the long run, but trying different approaches does highlight the impacts and the handling profile of each method.

Looking at the now-gathered data, one thing was obvious - can't do dieting because it is not doable to have a shopping list and meals for me and another for the family.
Gym is also off the table - too much overhead. I spend more time on the trip there and back than actually there.
And home exercise equipment is either super crappy or very expensive. But it is also the most reasonable approach.

So it is solutions time. I got a nice exercise bycicle (not a peloton), an yoga mat (the wife already had that one) and an exercise program that uses only those two resources. Not as efficient without dieting, not as measurable and broad as the gym, but it fits my workflow. Deploy to production!

A few months pass and the dataset grows. The signal is subtle but has support - it works! The handling, however, needs improvement, since I cannot often enough get with the exercise program. Some mornings are just after some hard days.

I start thinking about what else I can improve in the program, but it is already pretty lean and full of compromises.
So I pull an engineer and start thinking about the support systems and draft profile. What else could be draining my willpower and morning time?

Chores. Getting the kids ready for school, firing up the moka pot, setting the off-brand roomba, folding the overnight-dried clothes, cooking breakfast, doing the dishes, cleaning the toilets. All part of my morning routine. It might benefit from some automation.

Last month I got that machine our elders call "wasteful" and "useless crap lazy entitled Americans invented because they feel oh-so-insulted for simply doing something by hand like everyone always did" - a "dish-washer".
Heh, I remember how hard was to convince my mother-in-law that an remote-controled electric garage door would not make she look like an spoiled brat.
Still to early to call, but I think that the dishwasher just saved me about 25 mins every morning. It might be enough to save willpower for me to do more exercise.

This is all so reflective of all data analytics cases really are out in the wild - the analytics phase seems so small compared to the gathering and practical problem-solving all around. And yet d.a. is what tells you that you are doing the wrong thing all along. Or on what you should work next.

> be me
> studying 1.5 years liberal arts stuff and general education class at community college
> transfer to a 4 year university.
> realize I need a major
> Realize I also I wanted to 9ne day have a family.
> realize family would need money
> "struggling actor" not a great choice
> pray about what I should be doing
> get distinct impression that instead of attending the session on majors at the college of fine and performance arts to go to session with the college of Science and engineering.
> hear pitch for computer science.
> signup for introduction to programming taught with c++.
> A couple semesters down the line take 3 classes all at once Discrete Math 1, Linear Algebra, and database design and administration.
> around week 6 realize that all 3 classes revolved around sets and set logic and set math.
> realize rdbs's are "applied" set math and that Each class a little more "applied" than the former.
> Be genius at SQL and set math
> havereally smart database teacher mentored me
> get introduced to the recruiter at the career fair.
> get interviews
> get flown out for 2md interview
> get internship
> do work, and get project back under budget
> a job offer
> finish senior year
> start as a "real" developer supporting business data and analytics.
> ???
> profit.

Clustering high dimensional data - SOS!

I have to cluster documents. I computed the tf*idf, but I have ~45K docs with 28K words.
I did minibatch kmeans which works alright, but everything else runs forever. I need to compare 2 clustering algorithm, so I need at least another one that works. In this life time.
Suggestions?

Was training a model for an hour on paid GPU after which it showed a deprecation error and crashed my Jupyter notebook.

Husband looking into online schools for CS. Anything data science related. He loves math (and is freaking good at it) and teaches himself R for fun.

I put 0 thought into my own schools (terrible, I know, but not likely to change any time soon). Any suggestions for good online data Science programs, with a math minor potentially?

It's for his bachelor's.

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.

I need to buy a laptop to replace my 5 year old one. My work is mostly in data science. My budget is really flexible. Any suggestions?

So as you may know, I am job hunting. One company I found, called ruby, sounded interesting (the name helped). They were looking for data science type stuff.

I was about to apply when I got the feeling I should check the description. They were boasting about their flagship product.

Ashley Madison.

Needless to say, I burst out laughing and moved on.

I started iOS app dev thinking there’s good scope in the future,now I hear people saying app dev is gonna die switch to data science. Tf

I have a course at my university about personal data and it feels more than a law course than a computer science one. I asked the teacher why do we have to be taught that subject and how would we be able to use what we learn in real life and she got triggered, telling me that with just by coding I won’t achieve anything and i have to learn more topics and if I didn’t want to be taught this subject why did i choose the university.
I just made a question you fuckin butthurt, chill the fuck out.

I spent 2 hours on Python logging system instead of doing real data science.
Really this module feels poorly designed.

Am I the only person here who thinks data science is awesome? 😬

In a mediocre job since last 4 years with just a developer designation, but we simply use Java based tools and products to do most of our job. Need to study for a change in job.

Literally every morning:
"Let me see what to focus on: JavaScript/Java/C++/Python/Data science/ML/AI/NodeJS/...." The list goes on.

Every Evening:
"I need to focus on Data Structures and Algorithms. So let me stick to Java for now."

Next Day:
Back to the same routine.

2 months have passed and I have not seriously studied or concentrated on anything :(

Depressed.

Learn modern Javascript, Python, data science, machine learning, to catch up and not be outdated

What is it about robot collected data that makes researchers so anal? Like, dude, it's not even personal data. It's literally robot's joint motor recordings. It's not nuclear data, so why the fuck do you protect it like your life and your country depend on it?

I hope you get fisted by that data every night and how it will end up in oblivion sooner because you didn't publish it. You asshole.

How many of you guys are developers who are transitioning to data science and machine learning? 🤔

what's your expirience with business intelligence / data science? Do your company has a own department for it?
If so how does it affect you?

Am I Data Engineer or Software Development Engineer ?

I design the infrastructure for analytics data, and I build the infra entirely including an development. Except making reports out of the data.

What I'm supposed to be called ?
Data Engineer ?
Software Development Engineer ?

Definitely not an Data Scientist. Official designation given by company is Data Engineer II. But what I'm ?

Confused, someone help me please.

I just received this.

"I'm just saying that one should be proud to be able to import libraries and call themselves Data Scientist who can apply machine learning."

What the actual fuck.

Got some stickers for my kaggle data science club..😇😇😇😇😇

True that

Why is python supposedly something big data people use ? Sounds like r and stats and well I don’t see the adoption of that though python is used somewhat I note in a lot of Linux apps and utilities

Just seems strange that an interpreted language would be used that way to me or am I an idiot ?

IEEE is full of shit! Why the fuck can't i download research papers when I have already paid for the subscription???
Fuckers, i didn't pay to view your old looking website!

2018: Data Scientist = Stack overflow copy pasting: "I followed a 12-hour 'DS' course on Lynda!"

lm() # science

Data science

Data Science MSc instead of Computer Science. Or realising that my first 4 years of work was as a Data Scientist and I should have asked to have my job title reflect that. Skipping faang, at least relatively early in my career (that's a whole thing I want to write about but not rn). Not spending a year out of work due to health problems & nearly dying.

It could have been better, but I've enjoyed it.

Today:

In the next three months, if I said jackshit about data science personal projects, you have my permission to backhand me into oblivion.

Need to stay on my current track...

I work with statistics/data analysis and web development. I study these subjects for almost a decade and now I have 4 years of practical experience.

This information is on my LinkedIn profile and from time to time tech recruiters contact me wanting to have an interview. I always accept because I find it a great way to practice interviews and talking in English, as it isn't my native language.

A remark that I always make to my colleagues wanting to start doing data analysis related work is that it may seem similar to development, but it's not. When you develop, your code work or not. It may be ugly, it may be full of security problems, but you almost always have a clear indication if things are functioning. It's possible to more or less correlate experience using a programming language with knowing how to develop.

Data science is different. You have to know what you are doing because the code will run even if you are doing something totally wrong. You have to know how to interpret the results and judge if they make sense. For this the mathematics and theory behind is as important as the programming language you use.

Ok, so I go to my first interview for a data science position. Then I discover that I will be interview by... a psychologist. A particularly old one. Yeah. Great start.

She proceeds to go through the most boring checklist of questions I ever saw. The first one? "Do you know Python?". At this point I'm questioning myself why I agreed to be interviewed. A few minutes later, a super cringy one: "Can you tell me an example of your amazing analytics skills?". I then proceed to explain what I wrote in the last two paragraphs to her. At this point is clear that she has no idea of what data science is and the company probably googled what they should expect from a candidate.

20 minutes later and the interview is over. A few days later I receive an email saying that I was not selected to continue with the recruitment process because I don't have enough experience.

In summary: an old psychologist with no idea on how data science works says I don't have experience on the subject based on a checklist that they probably google. The interview lasted less than 30 minutes.

Two weeks later another company interviews me, I gave basically the same answers and they absolutely liked what they heard. Since that day I stopped trying to understand what is expected from you on interviews.

Hey guys any advice/study plan for a 22 year old C++ Server developer to transition into data science ?

P.s. currently based in London

We specified a very optimistic setup for a data science platform for a client....

Minimum one machine with a 16 core CPU with 64GB RAM to process data.....

Client's IT department: Best we can do is an 8 core 16GB server.

Literally what I have on my laptop.

Data scientist doesn't use any out-of-memory data processing framework, e.g. Dask, despite telling him it's the best way to be economical on memory; ipykernel kills the computation anyway because it runs out of memory.

Data scientist has a 64GB machine himself so he says it's fine.

Purpose of the server: rendered pointless.

I want to do something data-science-y.
Gimme project ideas, and where can I get the data for it?

Also, not looking for machine learning, just basic data analysis stuff.

I'm bored.

Today I came across a very strange thing or a coincidence(maybe).
I was working on my predictive analytics project and I had registered on Kaggle(repository for datasets) long back and was searching on how to scrape websites, as I couldn't find any relevant dataset. So, while I was searching for ways to scrape a website, suddenly after visiting a few websites, I get notifications of a new email. And it was from Kaggle with the subject line
"How to Scrape a Tidy Dataset for Analysis"
Now I don't how to feel about it. Mixed feelings! It is either a wild coincidence, or Kaggle is tracking all the pages visited by the user. The latter makes more sense. By the way, Kaggle wasn't open in any of the tabs on my browser.

A bunch of people who know a bunch of frameworks but lack intrinsic understanding CS, therefore bringing the degeneration of overall quality.

This ultimately leads to:

1- shitty dev jobs (the future blue-collar job, always in risk to be automated)
OR
2- super high-end dev jobs (most likely AI engineering, devops, data science)

As generations pass, this shapes out a whole new world economy.

I am studying an online data science course in python offered by Microsoft.
The instructor uses Surface book and also has a Mac book on his desk for backup because windows.
He uses chrome all the time for his explanation to run jupyter.
The point is even they know their tech is shit but still "Windows has set your default browser to edge" - this happens
¯\_(ツ)_/⁻

Learning Data Science to predict the possible ending(s) of GOT.
Hell Yeah

Junior Software Developer Job( $37k-$42k USD)

-1 year experience
- J2EE, Javascript, HTML, XML, SQL
- object oriented design and implementation
- management of relational and non-relational such as Oracle, PostGreSQL and Cassandra
- Lifecycle and Agile methods
- Familiarity with the Eclipse development environment and with tools such as Hibernate, JMS, ,TomCat/Gemini/Jetty, OSGi.
• UNIX skills, including Bash or other scripting language
• Experience installing and configuring software packages
• ActiveMQ troubleshooting/knowledge
• Experience in scientific data processing and analytical science in general
• Automated testing tools and procedures, including JUnit testing, Selenium, etc.
• Experience in interfacing with scientific instrumentation, potentially over IP networks
• Familiarity with modern web development, user interface and other ever-evolving front-end
technologies, such as React, TypeScript, Material, Jest, etc.

I am betting they don't get many people applying.

!rant
Started Data Science course on big data universuty. The outcomes are heavily dependent on domain experts/stakeholders!!! Since all the answers are false positives and need to decide what make sense with the help of domain experts. And most of the Data scientists are not from programming background, they are domain experts who turned into Data scientists. Thoughts if I should continue with learning big data/data science, knowing that I have knowledge in information retrieval and search engines.

Just developer things ...

Source - Kaggle Cannabis Dataset

I'm a dev lead. I'm trying to consolidate a squad. There's a senior in it preaching the dream of career climbing and LinkedIn optimization.

Now all interns want to switch squads. I'm all for personal growth... but now everyone wants to be everything at once and productivity stalled. The job descriptions for our squad were perfectly clear, there's tons of different tech stacks... We can build a lot of cool things in this scope, and now no one can see them because Data Science or Data Engineering or Front-end is suddenly sparkling.

I'm tired.

That's cool I think yes / not :

Hey DevRant!

Not really a rant but a question:
I just got accepted into a coding bootcamp. Have any of you been involved in one? How was it? What would you do to make it a better experience throughout? Any advice or suggestions?

It's full time, six months long and I start in October and I want to make sure I make the most of the experience and absorb as much as possible.

I'm super happy that the course appears to be less just learning JavaScript and more involved in the Computer Science side of things, even including bits about C/C++, distributed systems, algorithms and data structures, software design/testing, cryptography, database management, and computer architecture. It also, of course, covers tons of resume work, interview practice, and networking.

Thanks!

We have been at a university of applied sciences today with our class.
It was kind of ok. I did expect more surprising things there. The whole building was smaller than our college (not the same as in the US). The rooms, where profs tell you things with a series of rows of seats, were dirty and pretty much used to the point that the seats are about to break easily.
I was expecting the university to be kind of the same as the universities you see in the movies lol.
It could have at least been bigger than our college and more "modern" than our school.
[...]
Anyways, let us get to the point here.
We were first in the foyer and afterwards in their main lecture hall.
We were introduced to the day's plans by a team of engaged students from different study programs and the president of the professors. Yada yada yada.
We got the full program in each room and each individual time span filled with study programs on a sheet of paper.
I did select pharmacy, media production, architecture, data science, applied computer science, computer engineering, mechanical engineering and future energies.
Pharmacy and data science were the most interesting study programs to me. I have asked one of the professors if deep learning was a topic for bachelor students, as well.
He said that that is only the usual case for people who got a promotion.
As an example he told me that yesterday he was at a conference hall with 10.000 people in which he gave a talk about deep learning. "Most of them were professors" he said. "Since this study program is new, it might change in a few years" he added to his conversation.

It is quite hard having to decide now.
Geo informatics and Aerospace Engineering did sound interesting, too.
There are a lot of things I would like to study at the same time haha.

Idk if I should just pick mechanical engineering first and add one or two after it to it. But that would take a lot of time. Geez.

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?

Fucking Django is the only project thaat claims to be for perfectionist but actually is a steaming pile of spaghetti code, data transfer objects, configuration objects and useless wrappers and shit. I mean this shits made by adults with computer science degrees how the fuck can they get that shit so wrong?

Today is my last coursework submission. I've touched on a lot of topics I never thought I would be able to do/even thought about. I like data science, but I just don't feel so passionate about it now. I just want to ditch coursework and do cool shit, but I never find the time.

Anyone else get somewhat "fed up" of what they've studied? How did you get through it? Just do the "cool shit"?

Story of a data scientist 😞

Spends 80% of the time trying to identify features, while the rest 20% worrying about identifying the features 😭

Just bombed my first quiz in Data structures & algorithms on induction. Fuck.
And the midterm is a week from today.

Anything related to UIs or data science
That, working with a spaghetti codebase, or unhelpful and not nice teammates

Tryna decide what I want my next job to be, I currently span some performance stuff, some data stuff. I'm torn between going hardcore c++ high performance compute or pure data science.

Come to a weekly deep learning meet up this morning 8.30AM. The event start at 10 AM.  While waiting I read news and play some game. As time near 10 o'clock I had strange feeling: The guest room so quiet, just me and 2 security guy.

Okay I think comittee that run this event a bit late because of traffc jam and I wait more. In the end the committee didn’t even show until 10.30AM. Later I found on another data science group today's event is postponed and I go home.

WHY DIDNT YOU GUYS MAKE ANNOUNCEMENT ON SLACK? YOU WASTE MY TIME WAITING 2 HOURS

What are some job possibilities for software engineers that are a bit more challenging?

Software Engineering just became routine and with all the hin abstractions during the past years it’s not really a complex job anymore.

Thoughtful about data science but I think I’d get bored with that as well after a few years.

Looking for ideas with:
- technical skills
- have a lot if responsibility
- at least same pay

Would be interested in e.g. investment banking but that seems far out of my league (education wise)..

So after a couple years working at this company, the faculty I graduated from introduced a postgrad (masters) course in data science. I was always interested in the field, so I said fuck it and jumped the bandwagon...

I'm starting this week, I'm kinda worried my knowledge of maths and statistics got a bit rusty since graduation. Also most students there will be 4 years younger than me, and I'll keep doing my full-time job at the same time. But hey, at least I'll break the routine, and I can always quit my job if it turns out I can't do both, so whatever.

That's all folks!

Let’s just face it. Once the majority of people understand, data science (machine learning on custom behaviour mostly) will be the most disgusted job in the world. Mind boggling! You get shot right between the eye by doing it.

"""Itty bitty frustration"""

# wannabe mode on

import sklearn
iris_dataset = sklearn.datasets.load_iris()

ATTENTION PLEASE! Important announcement following:

Please check your interface implementations for correct byteorder according specification BEFORE YOU START COMPLAINING ABOUT DATA FAILURES ON EXCHANGING DATA.

Freakin hell, if I'd get some money for every byte order mismatch on testing interfaces, I'd be a be a billionaire.

And why are all those highlevel I-know-every-fucking-framework developer incapable of checking the real memory content of a datatype, and the real data content on the interface even if you tell them that their byte order is obviously wrong?
No, your system is not the centre of the universe and I don't care how you get your less-than-32bit-datatypes-are-for-assembler-usage-frameworks to change byteorder. It's not rocket science, if there's no ready-to-use-function then write those 4 lines yourself.

Next time I get to specify an interface I'll go for mixed-endian, just to make sure everybody involved knows the concepts of endianess afterwards.

Anybody have any great tutorials about web scraping with python? The data science courses I took only covered maipulauting and visualizing data not getting it.

Hi guys i need to vent with you. I live in Portugal.I graduated in computer science with 16 (0-20). While I was graduating I worked in my university programming for iot and big data fields. I have one article published in a scientific journal. I was looking for a job in my country, and I have gone to 5 interviews where they wanted to pay me about 700 maximum because they say this is my first job. The house rent is about 300 and with food and daily needs I can't have money to simple things in life. It's sad that companies don't give value to people they just think in money. It's sad that our work and knowledge is not valued...

Hey all, can you guys recommend some great books on database theory and design. Something aimed towards intermediate towards advanced. It doesn't have to be sql, I just want to learn how to make a kick a#@ db.
Thanks!!!!!!!

I have statistics joke but it's not significant.

Data scientists unite!
I am working on a face recognition solution to identify and tag different faces in real time and currently using chinese whispers algorithm for clustring. The more I think about it the more inadequate it sounds (number of faces encoded increase over time thus the complexity). I've heard about YOLO but cant really decide. Please enlighten me!

Why the fuck do you ask Data Structures and SQL queries for a Data Science interview?

I feel pity on those companies who evaluate people based on the above for DS position.

My worst fight with a dev was definitely that time I tried to break the mould and build this incredibly tedious VB app to automate data handling through Excel, PowerPoint and Outlook. The other dev always said "you can do this" and "come on, it's not rocket science" and I was always like "yeah, dude, sure, but can you help me with this bit here, please, I'm so stuck on it?" He'd be all like "ofc bro, I got your back", but when it came to the actual work that needed to be done, he was all silent. Needless to say, now I have a rubber ducky to help me with my dev needs, as talking to myself felt like a nightmare. Guess that's what other people feel like when I strike up a conversation with them, too.

So I have question about my resume.
During my college time, I have done two projects related to politics:
One is to analyze the bias of media. What I did is scrape news covers for Trump and Hillary during election year and get sentiment analysis. The result is not surprising that among NY Times, NBC, Fox, Eashington Post, and CNN, Fox news is clearly favoring Trump, since Fox news is a republican news site.
The other project I did was to analyze the speech complexity and sentiment of the election. One of the observation we made was that Hillary and Trump are almost at the same level regarding speech complexity. However, Trump has a more positive sentiment in the speech, which is true consider how much he loves to say make America great again.

Now the question is, when I gave my advisor my resume, she said that I'd better not put those two projects on my resume since they are related to politics.

But, I am applying for a data science master degree. Seriously, I was just collecting the data and the data speaks for himself, why should I take those projects off my resume? I'm very proud of those projects I did as a matter of fact.

So here is the question. Shall I take off those two projects on my resume because they were political or I should leave it thereawarreally need some professional views. Please.

hey guys, im a total noob and new to this field. this post is open for criticism and suggestions.

so i wanna forecast slippage (dependent) using the % WT Plan (planned work, the predictor).

i get -0.35 for correlation.

and im using knn regression

how does this look to you? insights and comments are appreciated. thanks!

When you wanna be a Data Scientist and always land into internships where you are assigned with web development...
Learnt Node, Flask, Spring frameworks across different internshis...

I thought the field of Data Science was plagued with frauds, then I met "Data Science Recruiters."

R or python for data science?

The gap of data science in industry and academia is so large. As a data scientist in a large financial company, I see that people are still using traditional models such as linear regression and SVM, while people in academia keep inventing new concepts and techniques such as deep learning.

I am not saying that we should completely embrace deep learning, or stick to classic methods. But I just feel so surprised that the gap is so large...Sometimes I am even thinking whether I am doing the right "data science"...

Never underestimate the power of a misplaced static in your Java to totally fuck you over.

I was busy with my computer science project for the semester where we have to implement a Sudoku solver without backtracking by using graph theory.

So there I was writing my data structure for the grid when for some reason all the cells were initialized with the value 8.

After a whole night of debugging I was about to start over when I realized I had made my array static.

And boom, it works. WTF!!!!!!!

Old one but popped into my mind today,

during 3rd year project, when all computer science students were mixed together,

I wrote the design / implementation doc

had a lot of acronyms as it was a technical course

referenced VS IDE

Idiot on team came along and decided to expand these acronyms

IDE became Intercompany Data Exchange

I lost the plot as he submitted it before i proof read the thing!

*face palm

tl;dr
that moment was a full semester

full
I was an Electrical Engineering major taking a Data Structures class and for the first time, I understood the title computer SCIENCE. In EE, you just blueprint all day long, but you never build anything. In CS you build and blueprint at the same time.

When professors rely on YouTube to teach you the syllabus, you know this is our education system **

#India

Dirty data? More like dirty laundry! And don't even get me started on explaining complex models to non-techies. It's like trying to teach a cat to do calculus. Furr-get about it!

Data scientists should be charged with animal trafficking and animal abuse because they import Pandas 🐼 and feed them to Python 🐍

So today in school I decided on my career choice. So I've decided on becoming a data scientist because I can still use my programming and I very much do like looking at data and researching things as well as program obviously :) so if there are any data scientists or data miners out there do you have advice?

I'm not a data scientist but lately I've learned NumPy, Pandas and now I'm learning Matplotlib and Seaborn and after years of Excel the improvement is astounding.

Excel is far easier to approach (I casually use it since I was 6) but once you need to do more advanced stuff it requires a lot of tricks and workarounds which needs to be memorized and are hard to find just by reasoning or are straight impossible without the use of macros which introduces many compatibility issues.

Pandas on the other hand is harder to approach but once you learn the concepts between its basic data structures you can do a lot with little "Google-Fu".