OP has a point, if I want to learn PRACTICAL front end programming, I will choose javascript, not Python. Same for Neural networks, just switch the place.
To deploy a model in js (as a web page) all you need is a static S3 or GCS bucket. You don't even need a webserver and it can automatically handle infinite scale. Show me a python solution that can do the same.
First of all, what you have described is far from the reality.
Had this come true, only inference will be in javascript, through some language agnostic standardized model format, not training. The model is just a blackbox function for the js runtime to call. The amount of javascript to make this happen will be surprisingly slim anyway.
Did you try any of the links I included? This is the reality for all of them and they are a few years old. They have a model file loaded from bucket url and never make another network request thereafter.
It's actually the recommended workflow from https://js.tensorflow.org/ where you'd find tons of other examples.
But you're right, this is for inference only. I would not do training in JS.
JS is faster than Python, but in the land of DL, there is C++ and everyone else. No one is using Python to do the actual computation anyway.
Depends what "actual" computation is. If you're definition of "actual computation" is something which requires extreme optimization then your definition precludes the question. In the real world there is an extraordinary amount of computation done with inefficient languages though simply because development time costs very often outweighs run time costs.
