| I don't think there's a master plan or a design idea about that. There's an old saying that goes like "Python is the second best language for anything". Python isn't the best for any kind of task; but you can do almost anything in any field with python and some libraries. It's reasonably easy for a non-programmer to use it. I think my first experience with GPU programming was using CUDA with C (I think it was kind of customized C in mid-2000s), so Python is not there since forever. But if you need to do a bit of web scraping/input data manipulation, a bit of "offering a gui" (e.g. a small web server that shows the data), a bit a of matrix/vectorized operations, a bit of model training or even just inference... python has everything and everything is reasonably good. At least some of those operations would be cumbersome in other programming languages. Try using R for general-purpose programming. Or Java for number crunching/matrix operations. They just suck. Try finding the "greatest common divisor", functionality-wise, for the many tasks that you need in a ML system (just as many other systems), and you'll find Python. The drawback is, IMHO, that it doesn't "scale" well. Python makes great proof of concepts and prototypes, but I'll always pick a different stack (possibly with multiple languages and technologies) if I want a long-running, maintainable production system. |