2010: PHP, CSS, Vanilla JS, and a LAMP Server.

Ah, the simple life.

2016: Node.js, React, Vue, Angular, AngularJS, Polymer, Sass, Less, Gulp, Bower, Grunt.

I can't handle this, I'm shifting domains to Machine Learning.

2017: Numpy, Scipy, TensorFlow, Theano, Keras, Torch, CNNs, RNNs, GANs and LOTS AND LOTS OF MATH!

Okay, okay. Calm down there fella.
JavaScript doesn't seem that complicated now, does it? 🙈

sudo apt-get random-tool

Traceback (most recent call last):

Aborting because there's a fork in the spoon compartment on line 43 in main

Error this script only works on Python 2.7 and maybe 4.1 on line 59 in main

Missing symbols when trying to decipher Sumerian recipe for steamed vegetables on line 67 in main

Cannot open shared object: Your OS is a bully and is hiding my files on line 98 in main

Are you sure all directories matching ^(/)?([^/\0]+(/)?)+$ are in your $PATH on line 268 in main

Your computer is kind of vibrating in an annoying way on line 332 in main

Failing because I'm feeling insecure please hold me on line 587 in main

I'm feeling confused about my sentience when running TensorFlow models on line 682 in main

FUCK

HAS ANYONE EVER MANAGED TO JUST FUCKING INSTALL A PYTHON BASED APPLICATION WITHOUT DEBUGGING RANDOM COMPUTER STATE SHIT AND DEPENDENCIES FOR THREE HOURS?

“UR HIRED”

I am trying to understand something for a while. devRant is full of privacy advocates and to be honest, part of it is almost taken by a group of people that call other people random swear words people because they are using a particular product of a company.

I will raise some points and will try to discuss them with other people in comments.

I will stick with Google. Since it looks like it's the most hated one. A company that has built one of the most intelligent infrastructure, the most popular mobile operating system and of course, the best search engine currently available.

The problem everyone sees is the privacy. Google tracks the search history to give users a better experience and show relevant ads. You might not need this "better experience". In case you don't know, you can turn off personalized search any time to make sure Google doesn't track. Same goes with Google Chrome, you can turn off all the data it is sending to servers in settings. You can simply not sign in if you don't anything to be synchronised.

An argument is Google should be opt-in rather than opt-out. But the general users are not tech-savvy. And yes, going to settings and turning on personalised search is a lot of work for a huge amount of people. Trust me, I worked in IT before. If they find other search engine giving them a good experience without changing anything in the settings, they will just simply move to that engine.

What interests me most if how people back DuckDuckGo. First of all, not all parts of DDG is not open source (it's fucking not, you can argue all day). Parts of it is closed because of licensing issues.

That is perfectly fine to privacy community. But it's not when Chrome is closed source for almost the same reason. I mean when you're using DDG, you are supporting a US-based company that has privacy all over its face and using closed source application on their server. Have you not learned anything from history?

You might be wondering about my obsession with Google. It hurts me when I see a giant company whose popular software is open source is bashed like this. Google has made huge contributions to open source communities. Chromium, Android, Kubernetes, Angular, GoLang, TensorFlow etc.

And PRISM, how do you know that DDG is not part of it? it's US-based after all.

I just saw an article that used a video with a title "TNW - Aral Balkan - Free Is A Lie | The Next Web" while asking us to switch to DDG. Ummm....DDG is also free right?

Maybe we should raise concerns with the US gov first rather than Google.

Very specific and annoying situation here:

- Working on a machine learning project with other people
- I'm on Linux, they use Windows
- We code in python
- We generally use vscode for development, and its python extension

I implement some basic neural networks with tensorflow, and add a bunch of logging for it. I test it on my machine and it works fine.
But, my group mates report that "after a few seconds the entire client hangs".
Apparently it only happens on Windows?
We start debugging the hell out of the code I implemented, added 20 log messages and sat there for a solid hour.

Until I make one very odd realization: the issue doesn't happen when I run the script in my terminal, instead of vscode with the debugger. So I try different debug settings, using an external terminal instead of vscode's built in debug console seems to fix it too.
And I make another observation: In the debug console, some messages don't seem to appear at all, while the external terminal shows them just fine.

So, turns out, that printing an epsilon character: “ε” (U+03B5), causes the entire thing to hang up.

It's the year 2020 and somehow we still can't do unicode.
I'm so done, what on earth.

Ahh, tensorflow.. Why so hard :'(

Arrived today!
I'm using C++ for machine learning purposes using TensorFlow and OpenCV (rip Python, you are too slow 😭)

What are you using C++ for? 😁

Remember the super duper company I applied for? (Last rant)

Well, I did their coding challenge. And after many years I had to do a metric crapton of C++. It's not a fun language. It's frustrating how human-unfriendly it is, and maybe one reason why I low-key like it.

Anyways, here's hoping that I didn't fuck up too much.

On a side note, I realized tensorflow actually has a cpp api. I think I'm gonna work with that in my next mental breakdown. 🧐

Deep learning frameworks war.

Today I learned how to break captcha using tensorflow !
Wondering what is the use of captcha while it can be broken so easily?

GPU: *exists*
TensorFlow:

So I started learning TensorFlow ... !!
... Boy oh boy... I have a greater appreciation for AI developer now !!

Frustrated, tired and a bit lost.

I'm a "Senior PHP Backend Dev", which includes not the greatest tech stack nor the best job title, but it pays fine, and the company is awesome to work for.

I suck at writing features, but I'm great at bitching, and I easily put complex abstract concepts into usable models. So I'm also QA, tester, tech lead, database architect, whatever.

That makes writing PHP less annoying, because I create the rules, and whip devs around when they forget a return type definition or forget to handle an edge case. But I don't write a lot of code anymore, I mostly read (bad) code.

Lately I REALLY feel like doing something else... problem is that I know JS/ES6, but really dislike React/Vue and the whole crappy modern frontend toolchainchootrain of babelifyingwebpackingyarnballs. I know Python/Tensorflow/etc, but don't feel like I want to go into data science or AI. And then I'm awesome at the shit no one uses, like Haskell, Go and Rust (and worse).

I got a job offer which combines a very interesting PHP codebase with a Java infrastructure, where I could learn a lot... and I'm kind of tempted.

Problem is, everyone always shits on Java. I always made a bit of fun of Java myself. Don't even know exactly why, probably some really cruel instinct which causes kids to bully the least popular kid.

I know the basics, I've written the hello world, and a small backend app for a personal project. I know how strict and verbose it can be. I love the strictness in Haskell and Rust.... but those are both also quite terse.

Should I become a Java dev? I'm not talking about Android SDK, but an insane enterprise codebase at a life sciences corporation.

To the pro Java devs: What are the best and worst things about your job, about the weekly processes, about the toolchains? Have you ever considered other languages? Do you unconditionally love and believe in Java, or do you believe Swift, Kotlin, Scala or whatever will eventually make it completely obsolete?

Will Java hasten my decline into the cynical neckbeard I was always destined to be?

There are a lot more fun langauges, but looking at realistic demand and career value...

Trying to setup tensorflow-gpu on my Raspberry Pi.

Wish me luck.

AI robo revolution 😁

A Microservice Discord bot with a conversational AI using Tensorflow

Numpy and tensorflow eating my ram. I need to upgrade it. #8gigsnotenough

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

So... After reading up on the theoretical stuff earlier, I decided to make a real AI that can identify handguns and decide whether it's a revolver or a semiautomatic with 95 percent accuracy...

Well, basically, I been browsing my local gun store's online store for four hours for training data, killed a Mac mini while first training the system and I think I ended on the domestic terrorism watch list... Was that black sedan always there?

Anyway... It's working fairly accurate, my monkey wrench is a revolver by the way.

Isn't AI development a wonderful excuse for all kinds of shit?

"why do you have 5000 pictures of guns on your computer?" - "AI development"

"why did you wave around a gun in front of your web cam" - "AI development"

"why is there a 50 gram bag in your desk?" - "AI development"

Hmm... yeah well... I think it might work. I could have picked a less weird testing project, but... No.

error message of the day: "InvalidArgumentError: Expected dimension in the range [0, 0) but got 0"

......well, thanks google.

Are developers working at Google really this incompetent?
Seriously, during the years I've been working deeply and for long time with many software products developed by Google, like the Android SDK or TensorFlow for instance, I can't find a single feature in them that isn't foundamentally wrong and badly designed starting form the basis, clearly due to an evident lack of the most basic programming knowledges... Am I missing something? Are they secretly making anyone out there think they are dumb on purpose for some occult reason? Or is it truly a dumbness matter? I don't understand.. :(

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

I followed a tutorial on how to use TensorFlow to create digit recognition. It worked. Theres just a few issues ...

I found the code on a website, and wrote what i saw (almost copy paste)

I barely understood any of the code

I did not understand the results

I have no idea where the images was found

Im almost more confused now, than when i started, thats not good xD

When you finally get to use that tensorflow side project you've been working on for a while to solve a real world problem and your boss wants to know how it works.

Why am I such an average ?

It's just a sad realisation. Nobody cares but I wanna send this out there, just to write thoughts.. I am 18 in 3rd year of high school (grammar school so nothing IT related, basically waste of time) and in IT I'm all self taught but I feel like I could be better if I just didn't [something]..

I feel like I wanna learn so many things but when I look at you, it seems like a common problem in the IT sphere so hey, average guy joining the club.

I also feel dumb when programming. I didn't manage to learn C++ in it's entirety because to really accomplish something, you've got so many ways to do it and finding the best one requires deep understanding of the tools you've got at your disposal with the language and I feel like I'm not capable of this(self learn, in school/Uni that's different story).. But many (most) of you are. I've tried many coding challenges and when I got it working, I just saw how someone did it in one line just by layering functions that I've never heard of..

Also, we've got kinda specific national competition here in many fields including IT for high schools.. And the winners always do sometimes like "AI driven Life simulation" or "Self flying drone made from ATMega from scratch with 3D simulation in C# to it" or "Game engine" or whatever shit and it's always from grammar schools and never IT related schools.. They are like me. Maybe someone helped them, I don't know, but they are just so far away from me while I'm here struggling to get the basic level of math for any kind of machine learning..

Yeah I've written Neural Network from scratch in C but meh, honestly it's pretty basic stuff .. I'd rather understand derivatives which we're going to learn next year and I'm too lazy to learn it from khan academy because I always learn something else.. Like processing (actually codetrain started teaching tensorflow so that might be the light for me...) Or VHDL (guys you can create your own chip / CPU from scratch and it's not even hard and OMFG it's so fucking cool , full adder done yay) or RPi or commodore 64 assembly or game development with Godot and just meh..

I mean, this sounds exactly like not knowing what to do and doing nothing in the end. That was me like 6-12 months ago. Now I'm managing to pick 2-3 things and focus them and actually feel the progress.

But I lost track of the original point.. I didn't do anything special, every time I'm programming something, everyone does it better and I feel dumb. I will probably never do anything special, everyone around says "He's still learning he's genius" but they have no idea.

I mean, have you seen one of the newest videos on Google's YouTube channel (I openly hate them, but I will keep that away for now), something like "Sarah story" ? It's about girl that apparently didn't care about IT but self learned tensorflow on high school. I think it may be bullshit (like ALL of their videos ) but it's probably just fancied, not complete lie.

And again, here I am. I now C but I'm incapable of learning to program good which most of you did and are now doing for living. I'm incapable to do anything cool, just understanding what everybody else did and replicating it. I'm incapable of being clever.

Sorry, just misusing devrant to vent a bit

*My friend texting me*

Friend: wtf

My brain: w tf
My brain again: tf
My brain again: import tensorflow as tf

😂😂am brain dead

I work in a contract position and reviewed the code of a senior engineer recently. Regretfully I can't provide context to preserve anonymity.

He wrote awful JavaScript;

- handled a single DOM element with 2 different frontend libraries
- used the logical operator && to 'chain' two methods (it didn't work) instead of returning a boolean value,
- broke everything down into minute detail (a comment box had 7 components!),
- API calls were made for every component update instead of maintaining local component state where it made sense, which meant UI updates were slow,
- animated EVERYTHING, which made my Firefox on Xubuntu i7 64bit with 16GB RAM beg for mercy.

I had a rough couple of months with interviews, with 2nd stage technical interviewers throwing impossible tasks at me.

Example:

1. Create an online Python code editor with Javascript which can compile Python bytecode,
2. Use Mesos and Kafka to create real time architecture for Tensorflow with a Javascript frontend in 1 day. (I asked, and wasn't allowed to use Kubernetes or serverless architecture),
3. Hack a website from the browser's address bar using parameters ( what?!! ),

Obviously, the next time I meet a 'senior', I'm going to tell him talk is cheap;

'SHOW ME YOUR CODE.'

Hello Tensorflow !

"How we use Tensorflow, Blockchain, Cloud, nVidia GPU, Ethereum, Big Data, AI and Monkeys to do blah blah... "

So...lonely me decides to train AI with my ex's chats.... enough said. Happy new year 🙂

MARKETING IS A MENACE FOR SOCIETY and a large waste of time and resources.

Imagine that for some very stupid reason people were allowed to steal cell phones from unsuspecting victims and sell it on open market legally, tax invoices and all.

One could create a business like this. Steal some lad's brand new $600 iPhone and sell it for $280, because why not?

That is marketing. A company goes and makes a phone for lets say $180. Add in taxes, shipping and development costs, and we get to $300. Put some real nice profits on top (let's say 40%) and we get to $420.
The last 180 are the cost of marketing for society.

Today some stupid marketing conmen goosesteps into my lab and says that we must use Tensorflow and in-memory databases and multicloud redundancy and, I kid you not, "profound learning".
WE HAVE A FREAKING LOGISTICS OPS APPLICATION.
"We are putting it on the brochure, those technologies are set to sell well in our core market, and improve employer-branding" says the conmen.

A request for a feature is one thing, a request for an whole other technology because some snake-oil salesmen read the term in some clickbait rag and thinks that some starry-eyed moneyhead will pay extra because the brochure says "NOW WITH 2X MORE TECH!" is just an assault on society.

#machinelearning #ml #datascience #tensorflow #pytorch #matrices #ds

Fucking professors, they think could play ping pong with students. I started my thesis on ransomware but these meaningless biological creatures who is my relator sent me to another one who sent me to another one who sent me to the first professor. After almost three weeks I have nothing done so i switched professor and thesis argument to neural networks (TensorFlow, Theano, Keras, Caffe and other) and now they wants me back and one of them said that he is offended. Fucking retarded, I have to graduate and I'm working hard to do it in september, if you were a little bit interested I could have collect some material to study in august sacrifing even the summer but you mock me, but rightly it's my career and my money, it doesn't care to you. You deserve to get stuck in an infinite loop of pian.

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

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

TensorFlow's person detection is orgasmic and once I thought OpenCV was my love (tsk tsk)

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!

Compiling software on Linux:

Python interpreter? Easy peasy, just some dependencies here and there. Make does a good job.

Linux kernel? Piece of cake, 20 years of development will be freshly served on your machine after one hour compiling (I have a pretty powerful computer).

Tensorflow? Fuck this shit I am outta.

What is your story with self-built software? Which piece of code has the most terrible dependency hell?

Made the mistake of training my ML model in VirtualBox... Over 18 hours so far, and loss < 1 is nowhere near stable.

Does anyone else here hate people who use numpy panda and tensorflow and call themselves data scientists ??
Cuz I hate 'em. There are so many researchers who work day and night to figure out the math and algos which go into these libraries. These researchers are real data scientists.
If computerss sciemce would have been a religion, then just using these stupid libraries and claiming you are a data scientist would be blasphemy.

Anyone​ who likes Tensorflow ?

This happened while making a Love Live dataset

Dude. Tensorflow version changes are so fucking bad. It's even worse with keras because they create an echo chamber for shit. I'm trynna reset a fuckin model here, yet everything throws 99 more errors to the pile. Like, wtf?

***** For stackoverflow enthusiasts: found a solution, don't need your groundbreaking shit either.

Credits: Mritunjay

Keras was throwing errors...

Since I thought it was a tensorflow issue, I went up and down and all the way around. Installing all tensorflow shit like a bijillion times.

... But it wasn't. It was the fucking ipykernel...
It took me a good 5-6 hours.

I pulled a 12 hours day today.

... Somebody hug me plz 😢

I'm reinventing the wheel by making yet another neural network library. It's not any good yet but I learn as I go along.

The only documentation that exists now is the admittedly quite comprehensive code comments. I'm it because Keras (using TensorFlow) requires a 3.5 compute ability rating for CUDA acceleration (which I don't have) and it doesn't support OpenCL. Eventually, I will make my implementation support both with varying levels of acceleration for different compute capabilities with the oldest supported being my hardware. If I ever get around to it.

I'd say wish me luck but determination would be infinitely more useful.

How to install tensorflow on windows?
.
.
.
Uninstall windows
.
.
.
Install ubuntu
.
.
.
pip install tensorflow

Just installed Keras, theano, PyTorch and Tensorflow on Windows 10 with GPU and CUDA working...
Took me 2 days to do it on my PC, and then another two days of cryptic compiler errors to do it on my laptop. It takes an hour or so on Linux... But now all of my devices are ready to train some Deep Deep Learning models )
I don't think even here many people will understand the pain I had to go through, but I just had to share it somewhere since I am now overcome with peace and joy.

Tensorflow with Javascript 😂✌️

Get ur basics ri8... bruh!

Downloading a different version of python, for ONE FUCKING LIBRARY

Fuck you tensorflow

I love it when people say "I wanna play around with tensorflow".

TFW Internet speed is so slow & you have to download ton of packages

If PyTorch > Tensorflow:
print("True")

Output:
True
True
True
True
......
......
.....
True

Wait a minute? Is this a While True loop?
Doesn't look like an if condition xD

When you think you're ready to start with tensorflow and you end crying in a corner ...

Had some fun with textgenrnn (Tensorflow text generating thingy on Github). So I created a tiny dataset with some example c# code and let it train for a while.

Sorry people, but I ruined our jobs. We don't need to write code anymore.

Update: image was unreadable due to compression. Let me find an alternative.

Tensorflow in the browser... I'm not sure how I feel about this

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?

Pro tip: always make sure your methods return the correct variable.

I’m currently working with deep neural networks using tensorflow. I needed to generate some test data and wrote a program to create it. I had two text files which each consisted of approximately 5000 lines of text.

I wrote a method that should sort out some words, and make my final data shorter. When I executed the program first time on our server, it spent about 25 minutes, then crashed due to MemoryError (which in Python means that the server didn’t have enough ram). That seemed quite weird since I only had about 10k lines of text, and I even sorted out a bunch of it, and the server has 128gb ram, and nothing’s using it.

Apparently I returned the wrong variable. That meant that my program tried to save 750 quadrillion lines of text rather than just a few thousand.

Always make sure to return the correct variables!

Recently GitHub announced it is gonna preserve the world's open source code for next 1000 years. Great initiative! But someone has to take initiative to store StackOverflow data too! What if after 500 years someone tries to use Tensorflow and gets dimensionality issues? And imagine there won't be any StackOverflow to solve the issue.

Remember : Wherever there is a code, there is a bug.

I'm new to speech recognition game, so I was wondering what's the advantage of Tensorflow's audio recognition over Microsoft.Speech in Visual studio, if any.
Also open to any other suggestions/lectures on the matter.

Finally managed to get my CNN working with proper tensorboard logging. Think I'm starting to understand how it works.

But it got overfitted...

That moment, when you meet someone who haven't written even a simple if-else statement in their life and want to work on Deep Learning algorithms using TensorFlow. World is filled with so many ML crazy peoe.

i wrote a website, a server in go, a small os in c, a game in js, a game and server and web scraper and other desktop apps in java, mobile apps with flutter, a website with php also, implemented aes in go, wrote a parser in java. done sysadmin stuff on my vps and pihole/openvpn/nextcloud on my rpi. learn about c vulnerabilities and used metasploit. attempted to write an interpreted language. did some led displays with arduino. currently learning tensorflow.

i have never...
- written a driver
- made a game with a game engine
- created a file encoding
- implemented an oauth2 server
- made an api
- worked with vr

what am i missing? i want to be a very well rounded dev.

her: do your worst

me: *applies machine learning*

46 hours in.. Hope it's going to work!
What's your longest compile time?

I can't be arsed with jobs that mention tensorflow alone as their main tech.

If your company is willing to use tf and not keras, then y'all probably didn't understand what you're dealing with to begin with.

*Red flags and sirens in distance for bad designs*

Why is it that the tech Youtubers of this world (and tech reviewers in general) tend to completely skip development as a use case, and instead (if they do ever move off gaming) focus on things like Rendering & Modelling / CAD work? I'm sure there's *way* more devs in the world than CAD guys, surely?!

And if they *do* give it the light of day, it's always a quick benchmark based on "Firefox compile time", "Linux kernel compile time" or similar. Dude, it's 2020. Much as some would like to believe otherwise, most guys stopped compiling swathes of heavy C & C++ as part of their normal workflow over a decade ago.

Real-world tests I want to know about are things like docker performance, common IDE startup performance, compile performance of different sized applications on a bunch of langs like Kotlin, C#, Java, Clojure - or node.js performance, Tensorflow performance on NVidia's vs AMDs latest GPUs, etc. I care about how many IntelliJ instances & VMs I can have open way more than how many Chrome tabs I can forget to close.

But noooo - forget that, here's how fast Blender can render a BMW! 😬

Everyone I tell this to, thinks it’s cutting edge, but I see it as a stitched together mess. Regardless:

A micro-service based application that stages machine learning tasks, and is meant to be deployed on 4+ machines. Running with two message queues at its heart and several workers, each worker configured to run optimally for either heavy cpu or gpu tasks.

The technology stack includes rabbitmq, Redis, Postgres, tensorflow, torch and the services are written in nodejs, lua and python. All packaged as a Kubernetes application.

Worked on this for 9 months now. I was the only constant on the project, and the architecture design has been basically re-engineered by myself. Since the last guy underestimated the ask.

"Python" & TensorFlow (may be a bit later)

I tried to sort out a basic Multi layer neural network last night....by hand, just to prove that I was able to do the math by myself and understand that I have the intuition in control rather than just rely on Tensorflow or Pytorch to do shit for me.

I stayed up till 3 in the morning and woke up having nothing but dreams about the endeavor. Shitty part is that i couldn't stop dreaming about partial derivatives and how shit it was that I sucked at them in HS and uni. I get them now, but fuck I just feel that I could have done so much better at uni instead of passing my math classes with 80% to 90% of the grade. I feel as if I was slacking all thanks to being damn near mathematically dyslexic

TensorFlow, because it makes machine learning accessible to everyone.. and.. well, it gave birth to my Android counterpart <3

Giving a tensorflow workshop and the thing people struggle the most is the Linear Algebra behind it... it is only gradients in tensor and some matrix multiplication.

My recommendation is: do you want to work with Deep Learning algorithms? Y'all need Linear Algebra, not PhD, just a bit!

The feeling when you are very interested in Al, ML and want to do projects for college using tensorflow and openAI........
But you only have i3 with 4GB RAM plus 0 GPU.

That sucks.... 😶

Flutter.
Tensorflow.
PyTorch.
Back4App,
AppWrite,
Supabase,
Jitsi,
Signal,

Spent a few hours wrestling with AMD ROCm to get it working. Had to change my kernel a few times, install different versions of the rocm packages, and in one case selectively upgrade a package. I also need to run my programs with a few shady environment variable exports to work around some bugs. The whole thing looks shaky right now, nowhere near as simple as CUDA. Also, horrid names (seriously AMD, what's with the 3dgy names).

However once I got it working it works pretty well, happily training stuff via tensorflow-rocm, with decent performance. This is also probably a good project to contribute to, I'm nowhere close to AMD's engineers at this stuff but basic bug fixing and quality of life stuff are probably within reach.

Finally, after days of research and failures, I managed to understand and tweak TensorFlow's program for image classification.

The feel of power, arcane knowledge and fascination is just incredible.

Might not seem much these days, nobody was interested in it. But I, deep inside, knew: I was proud of myself.

Is there any good machine learning / unity3d online courses that you guys recommend?

Bought fucking nvidia gpu to test speed of some fucking machine learning models that generate speech.

6 hours wasted already for installing fucking dependencies
cuda, fucking tensorflow gpu, bezel and other shit

Fucking resetting password to download deb with cudnn,

really ??????? fucking emails are not delivered to my fucking mailbox

After mass click of send email and multiple account ban and unban I figured out I should login to nvidia website and then allow access to fucking developer every time I want to log in there - fuck shit

Uninstalling everything now looking for fucking compatible versions between software.

10 years in this business still fucking installation of dependencies is most difficult part

Fucking corporate business and their shitty installation instructions to fuck up peoples lives and switch them to the cloud.

Same was with fucking kubernetes

Fucking software dependency hell

It’s worse then ever before.

Fuck ....

!rant

So I trained this model, there must be the training gone wrong. Like how is a flat a Bottle?

Any Tensorflow developers here?

Used pip install to integrate tensorflow with python 3.5 on windows 10 machine but there were no models available in it. Had to download that separately and add it to tensorflow. Then tried using both inception and clasify_image.py but gives name error cannot find core. But when tested on python idle there were no error there. I don't want to custom create my own classifier but retrain the model. Any solution people?

Spent 2 days installing different versions of nvidia-driver, nvidia-cuda-toolkit, cudnn.
Disassembled pc due to some ram memory problems and pc not starting after freeze.
Looks like sometimes plug out and plug in various components on your motherboard fix pc lol. Destroyed PC casing that collapsed due to me sitting on it.

All of this to just find out tensorflow error and all crashes are from graphics card overheating after keeping it for some time at 82 celsius.

Added time.sleep to python code and looks like it's working, keeping temperature below 65 celsius.

Still ~100 times faster than cpu training so I can live with that.

Motherfucking piece of shit tensorflow, I fucking hate this piece of trash API fucking impossible to fucking use

Going through the stacktrace of my 30 line of Tensorflow code, made me surf almost 20 different library source codes.

Anyone know of any good reference material that teaches you how to implement and train your own Yolo object localization neural network? (Preferably for tensorflow) I'm not looking for pretrained models that you just downloaded and run, rather a tutorial that walks you step by step through the implementation of the network, the reasoning behind the architecture, and examples of the training data used for the training as well as the process of training?

I know it's a lot to ask but it's really frustrating when ever example is just "clone this repo, hit run and use the pretrained models" sure it might get you up and running quickly but it doesn't really teach you anything...

P.s. - seems like every educational post goes from super simple to super complex without any middle ground and the super complex stuff doesn't tell you why its used the way way it is.

I finally have nailed it make a working neural network for my data with tensorflow. Problem? It isn't satisfied with 10gb of my memory. Just 4 layers...

What is the role of @tensorflow in Machine Learning and Artificial intelligence... 😀😀😀

The offizial guide to install Tensorflow(Python) on windows is BS. The stackoverflow solution only adds the package, but it wouldn't work.

Time to build it myself...

!rant

A (non tech) friend just showed me tensorflow and I am pretty intrigued. Has anyone here ever tried it and what have you done with it?

- Finish "Introduction to algorithms"
- Learn some genetic algorithms
- Get my hands dirty on reinforcement learning
- Learn more about data streaming application (My currently app is still using plain stupid REST to transport image). I don't know, maybe Kafka and RabbitMQ.
- Learn to implement some distributed system prototypes to get fitter at this topic. There must be more than REST for communicating between components.
- Implementing a searching module for my app with elastic search.
- Employ redis at sometime for background tasks.
- Get my handy dirty on some operating system concepts (Interprocess Communication, I am looking at you)
- Take a look at Assembly (I dont want to do much with Assembly, maybe just want to implement one or two programs to know how things work)
- Learn a bit of parallel computing with CUDA to know what the hell Tensorflow is doing with my graphic card.
- Maybe finishing my first research paper
- Pass my electrical engineering exam (I suck at EE)

Just Found pretty amazing stuffs with tensorflow and tensorboard.

It is great to have views and graphs of your training nodes

Trying to figure out the right version for Microsoft Visual Studio, Tensorflow, and Nvidia CUDA Toolkit has got me reaaaalllyyyy messed up!!!
Like the fuck!? One thing doesn't support the other's current version. It's like I'm playing a "version matching game, fucking candy crush shit!

It's so effing irritating!!!

fuck it, tell me straight.
Can i live into this tech world with poor math skills and no interest in web dev and designing?
my experience as native mobile dev was enjoyable and still is, but i fear that this is not a very broad career choice.
You see their is blockchain, dapps , hybrid apps, webapps, server designing, tensorflow models and Ai models( though they can be integrated with native apps too i guess ) , and many more tech and therefore jobs that rely on knowing about the webdev. and all i know is how to make a decent native java app.
and why the fuck should i join this web dev cult? its such a fucking mess. 8 different types of text sizes sizes, <b> and <strong> being the same thing, do you know about a thing called abstraction? My android studio would give me fucking murder warnings if i even dared to introduce hard coded texts along with code. and here, an html page is basically text + attributes? fucking kill me.

So I get an internship and I am obviously very happy about it.
First day at work and I get a brief idea of what my project is and it was related to machine learning with tensorflow which I have experience with.
Come tensorflow lite and NN api, my job is now to convert tensorflow model into tfLite and use NN api whichpart of NDK and I have 0 clue about it.
So I obviously go to documentation and read up about it. Goes to Google sample to checkout NNAPI example and I freak out looking at the no of files and the code cuz. Wtf are these JAVA CPP WRAPPER AND NATIVE CODE .HOW DO I EVEN START WRITING CODE FOR IT. WHERE DO I BEGIN. HOW DO I USE NDK WITH THIS. THERE ARE NO OTHER EXAMPLES ON THIS REEEEEEEE
Legit feel like quitting already

What I want to read is how to train an ai model to recognize images.

What I don't want to read is your 6000 word ad filled dissertation on everything related to the concept of ai that links to the tensorflow documentation 3/4 of the way through.

The first 15 links on Google are like this. You have you look real hard for a link to the actual documentation.

SEO has absolutely ruined the usefulness of the internet.

Listing my skills:
I have published react-native apps.
I can build an extensive backend/API thing with node.JS/a good framework.(worked on something for my countries national football league during an internship as main/only dev)
I have some experience with c# but havent used it since school.
I have no issue getting into new frameworks/languages, as long as its not PHP.

I have experience working in software teams.
I have experience running my own company(Online store selling airsoft supplies - i quit).

Im working towards getting familiar with Tensorflow 2.0.
I have a Cambridge English assessment certificate at grade C2.

I am currently working(for 0 pay for 50% of the shares) on developing a social media app that uses location tracking on a 20-200 meter scale.

I have ADHD and have been spoken on/warned due to its effects( i.e. forgetting to report progress, getting distracted, needing stimulation so i browse youtube(even have it playing in the bottom corner sometimes), poor communication.

Am i worth anything at all as a developer... im getting pretty depressed due to not having an income at this point... and I dont think anyone will hire me

I have a system design question I was hoping u guys could help me with.

So I want to make a display that shows an animated wallpaper. I want to have a camera in the display that will recognize finger gestures and will change the wallpaper accordingly (shuffle to a new one, etc.)
EX: when the current wallpaper is displaying, when the user shows the camera the peace sign, it will switch the current wallpaper to a random wallpaper.

I used tensorflow and the mediapipe hands library to get the finger gesture recognition to work. I used tensorflow, python, and openCV.

Now that the finger gesture recognition is finished, I moved to the animated wallpapers and I made a couple with p5js.

How could I best combine the two? Should I switch from tensorflow in python to tensorflow.js? Or should I find a way to re-do my animated wallpapers in python?

My original plan was having the foundation of the whole system be python. This is so I can have the finger gesture recognition run on the main thread, and have another thread deal with the wallpapers.

Let me know if u guys have any ideas or if I’m not clear. Thanks!!!

I'm thinking I should learn a ML framework/platform (Tensorflow, Azure, ???).

Which should I choose? The only thing I can think of doing with it tho is to build a tic-tac-toe or maybe a gomoku AI...

Trying to get Darkflow running on Windows is an absolute nightmare of endless debugging. Now I understand why everyone's been using Linux distributions for Tensorflow stuff.

Master thesis in ML 2018: successfully followed the "Deep MNIST for Experts" TensorFlow guide

It's not a real dev regret but it's related to it: Not being able to fix a price or a value for my skills.
It's a real regret.
Just coming out of college I have tried my hand at freelancing at found it real hard to fix a value for what work was offered because I just found it weird to fix a monetary value on something that I've done for free for my entire life ( at school and uni I mean).
To make it worse my first experience was with a grad student who wanted me to complete her project.
Now being from India, I know that we have a stereotype of doing work for a lower price.
But this girl took the cake.
She wanted me to create a custom Image classifier using tensorflow.
It had to train with live images and then detect those images in the live video feed.
It's quite simple but still training the basic network(which would be used to just detect features) would take a decent amount of time and effort.
No pre trained models was also a prerequisite for her.
After hearing all her requirements I asked her what price she was willing to pay.
She said 50$ lump sum.
Being really confused as to what to say to that I just stopped replying.
To this day I have no clue what would be a reasonable price to quote a client like that.
After that I just continued dealing with people I knew personally and am currently doing that as an internship. But entering the proper freelancing system again has become a kinda weird thing in my head now, since I have no clue as to what price to put on my skills.
Is there any advice that any of the more experienced people would give?
Also consider the fact that I'm relatively fresh out of college and have no corporate experience.
Even if you've read my rant and have no advice it's okay. I guess this is a path of self realization after all.

Q: How easy is it to create machine learning models nowadays?

= TensorFlow

That's ML commoditization.

Anyone tell me the all in one website for programming similar to tutorialspoint. 😊

Because tutorials point has no any update regarding Machine Learning and latest package of python tensorflow.

What actual pain is, trying to install CUDA on Windows (that should be a pain there itself) and all after 3 hours you realize your lappie doesn't support it (Geforce 820M)! There goes my dream of Theano, PyCuda and Tensorflow-gpu ...

What tools do you have access to at work?

I don't work a tech company, far from it. I love it but both the hardware and software at my disposal are so shitty I'm starting to lose it.

Running Windows locally, I'm not allowed any Linux distro because "security." Indeed, I don't even have admin rights on my machine. It was rejected. The excuse being that I am sudoer on a server, which (and can only be) physically located in our headquarters.

Today I found out this server's CPU from the dark ages does not support tensorflow, so here I will be building that shit from source tomorrow (no GPU of course).

And thanks for 4G of RAM on what you refer to as a "power" machine.

Can I blame Trump that my handwriting recognition engine is only predicting at 80%?

What are the cool things about Tensorflow?

I just start reading about tensorflow.

Is it a crazy idea to train a model with about 40 classes?

How much images should I use at least for one class?

Ehh... too deep too fast?

What's a good book for learning Tensorflow... and maybe ML Basics through usages/examples?

Can I use TF, ML without the math/lin alg? cuz idon't have that and don't really wamt to learn unless you can convince me otherwise **through usages/examples**

Has anyone (who does either Data Analysis, ML/DL, NLP) had issues using AMD GPUs?
I'm wondering if it's even worth considering or if it's too early to think about investing in computers with such GPUs.

I have a question about how to set up TensorFlow and use Node.JS for MongoDB CRUD. Help!

Cool, have that question on StackOverflow, because this isn't. If you have nothing to rant about you probably are still missing uncountable hours in training to get on a level where you can rant. Fuck off. Choke on a horse dildo. Get it through your thick idiot skull that devRant isn't your beginners bingo bongo chit chat.

Cool TensorFlow.js project for someone who wants to learn TensorFlow and is out of imagination?

where to get EMNIST dataset in PNG format?

Developing a universal language model using Tensorflow; gotta love AI.

I feel really lost in neural network theory.
the mnist sample made sense, but now I'm looking at Gans and CNN's.. and now all of a sudden I'm lost.

True also are the examples I'm finding of something I know I was able to get to work when more at peace once upon a time called wavenet for text to speech.

I used the Onyx model however which was very easy to implement, but I quickly get lost looking at the tensorflow and pytorch code, even though it is very short I feel intimidated.

The ssd mobilenet documentation also is pretty straightforward, but when I look for wavenet information about providing input in what format and interpreting output I'm having some trouble.

Its frustrating.
I'm tense, I'm poorly rested, I'm sick of having to redo crap and I'm surrounded by people who make me hypervigilant, skin crawly and tense.

How to overcome these things when I'm not at peace at all ?

I don't know. Pushing through it isn't compatable with the mindset I've been forced into.

How do i run tensorflow with amd gpu?
any hacks?

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.

Fucking test, son of a bug I made you finally green. Test Driven Data Science induced RAGE.

CNTK or Tensorflow?

Is it possible to follow a TensorFlow guide/tutorial without complex mathematics knowledge?

Is tensorflow unintuitive?

anyone done the tensorflow developer certification exam?

Android studio has a mini version of TensorFlow,
Me: makes an AI Gallery Vault
Gets Notification: "Seems like you have a spouse and there are inappropriate pictures in your photos and downloads that could potentially start a fight, do you want to automatically hide them?"

Hello everyone. I'm getting interested in neural networks and I am trying to install the TensorFlow machine learning API using Python's pip package manager but it gives me an error saying that the package couldn't be found. I made sure that I spelled everything correctly and tried using VirtualENV to install it as well, and I uninstalled Python 3.7 and installed 3.6.4. Could anyone help me?

I'm new in deep learning world, I want to develop a project regarding live text detection on mobile camera (without taking an image by the camera), can I do it by the tesorflow object detection api ? or with anyother tensorflow api or with opencv, which way is best? other suggestions are also welcome.

I feel google's move to cater ML and AI resource to everyone for free is a complete sham. I believe it's a very shrewd move to promote TensorFlow and google cloud. What do you think !??

Who on earth decided, that float64 is a suitable default datatype for one-hot vectors in numpy?
That's what I deserve for relying on reasonable implicit behaviour

GCP is overrated. Use Raspberry Pi for ML

Actual screenshot of TensorFlow getting started section. Nicely done, Google.

how do i get the installed numpy version for tensorflow that pip autoinstalled to not interfere with opencv which requires numpy >=1.2.0 ?
which btw i just installed.
and why is tensorflow a piece of crap ? LOL

Interesting NY Times article today Saturday March 26 2016 by Markoff and Lohr, "A Race to Take Control of Artificial Intelligence And the Future of Tech". Lots of C levels will read this article and ask CIO if AI on radar. Will fan the fire. Also a lot of VC action. Google TensorFlow open source. Microsoft also all in and of course IBM Watson. Google beat Go grandmaster 4-1, which is tougher than chess program. Something to keep on your radar. Have fun!

In our middle schools' science-type after school program we got a client from a hospital. We interviewed her on what kinds of problems she had in her workplace. She talked a lot about impaired vision and such. Most people were doing stuff like button extensions for people who can't feel well. I'm creating a NN for recognizing numbers. I trained the model to 99% accuracy and got to teach my friend about GitHub! Win win!

!rant

All things Machine Learning, especially Tensorflow

I am very interested in all the possibilities we have given the advances in this area.

Hey all, just want to say thanks in advance. Last night, my friend and I were in a project together (realtime), and I was teaching him about some basic Keras models in python, stacked with tensor flow. When we were at school the previous day, he was really interested in the actual concepts behind the code, but when we were actually making the model, he seemed kind of uninterested. I suspect he was just getting distracted, and its better to write down the code and go over it at school, but is there some way I can try and make it more fun/interesting for him?

Just started with Tensorflow and Python. Have a question, anybody willing to help?

Am I just an idiot for using a RedHat variant ?

Why is Bazel such a piece of crap and why do I have to use it to build Tensorflow ??

If you are required to do a custom Object Detector for Mobile.

Would rather use Tensorflow, Theano, or PyTorch to train the model?

Oh the frustration !
The confusion !
Tensorflow files why must you mock me ?!

Do you know a super simple guide / tutorial / etc to learn TensorFlow.js from scratch? (for real dummies)

Hey. So i really need help in getting started with tensorflow lite. Help in any way that you can. Thanks!

I am trying to decompose a 3D matrix using python library scikit-tensor. I managed to decompose my Tensor (with dimensions 100x50x5) into three matrices. My question is how can I compose the initial matrix again using the decomposed matrix produced with Tensor factorization? I want to check if the decomposition has any meaning. My code is the following:

import logging

from scipy.io.matlab import loadmat

from sktensor import dtensor, cp_als

import numpy as np

//Set logging to DEBUG to see CP-ALS information

logging.basicConfig(level=logging.DEBUG)

T = np.ones((400, 50))

T = dtensor(T)

P, fit, itr, exectimes = cp_als(T, 10, init='random')

// how can I re-compose the Matrix T? TA = np.dot(P.U[0], P.U[1].T)

I am using the canonical decomposition as provided from the scikit-tensor library function cp_als. Also what is the expected dimensionality of the decomposed matrices.

I was looking for job from some months to now. Im Junior, I know Backend Development and Machine Learning. im very well skilled in this subjects, currently im developing a deep learning model and deploying trough tensorflow serving and a Flask API. Im feel comfortable doing this, and i like it, but, this seems to no matter for any startup or company, i send lot of application and got zero response. it is frustrating because i feel capable of doing stuff, but that no matter to anyone. Really disappointed

How much time will it take to learn docker?
I want to containerize python deep learning models, which you tensorflow and mxnet.

Pytorch va Tensorflow for someone getting into machine learning?

Does anyone know any good resources that walk you through building a image localization neural network(preferably in tensorflow)? Something that talks you through the though process behind the network design decisions and perhaps examples of training data used to train the network? It seems like every search result is just an example of how to download a premade network and it's weights which from a learning perspective is not very helpful. I'de really love to see one of the Yolo version walked through and trained but honestly any localization would be helpful.

Need some help here!!
I'm learning machine learning, so planning to buy Asus R510JX-DM230T. Are the below specs enough to practice TensorFlow ?? Specs : 2.6GHz Core i7 4720HQ processor

8GB DDR3 RAM, 1TB 5400rpm Serial ATA hard drive

15.6-inch FHD Anti-Glare Display, 2GB Nvidia GeForce GTX 950M Graphics

I'm a noob at Deep Learning. What should be my first project on it? Something I could publish as a paper. Ideas are welcomed :)