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? 🙈

My neural networks journey so far:
Look up tutorials -> see that Python is a popular tool for ML -> install Python -> pip install scipy -> breaks with some weird error involving BLAS library code -> spend half an hour fixing it -> try installing Theano -> breaks because my USERNAME HAS A SPACE IN IT LIKE SERIOUSLY? WTF -> make new account without a space in the name -> repeat till Theano -> run tests, found out that I didn't install CUDA support -> scrap the install and redo with CUDA support -> CUDA libraries take forever to download on shitty internet -> run tests -> breaks with some weird Theano compiler error -> go crying to friend -> friend tells me about Anaconda -> scrap the previous install and download Anaconda over shitty connection -> mess up conda environments because noobishness -> scrap, retry -> YESS I FINALLY GOT IT WORKING TIME TO DO SOME LEARNI-crap it's 4 in the morning already.

I realize that I'm a Python noob (and also, uni computers with GPUs have preconfigured Windows installed only, no Linux), but is installing Python libraries always such a pain? Am I doing something wrong? Installing via Anaconda felt like cheating, tbh.

>Be me
>Decide to contribute to an open source project for the first time
> Nothing big, just a simple compile error fix
>Make first ever pull request
>Over weekend pull request accepted
>feelsgoodman.jpg
>Take a look at recent commits
>Module I tweaked was finished in a commit 6 hours ago
>Fix no longer relevant

So close.. :(

Homebrew really hating upgrading SciPy to python3

I have started to work on pandas and numpy , should I work on scipy and sklearn or should make a strong fundamentals on numpy and pandas?

An open source technical graphing and analysis software using Matplotlib numpy and Scipy backends.

I love serverless functions but I'm so tired of complex orchestration, juggling event parameters and now scipy+numpy+pandas exceeds size limit of 250MB..

Feel like cramming it all in a monolith like the geezers of yore and be done with it

Anyone else here just hate how emotes are implemented in most apps? I love using emoticons but I despise bad emote icons. I wish there was a standard way in apps to revert emotes back to ascii and to have it show up to others that way, too. Similar to how bbcode had the [nobbc] tag >~<

God damn it!
Tried to use scipy's UniveriateSpline on some (x,y) coordinates that I have and it throws errors because I have multiple x values with different y value. UniveriateSpline expects all x values to be incresasing. Problem is I want to use these values, otherwise the result might be different than expected. B-Splines shouldn't be dependent on this condition or have I missed something in my studies? Documentation doesn't tell me anything.🙄