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0 pointsf1shy3y ago0 comments

TBH I was shocked by "Python for machine learning". I do not know where that comes from. Maybe because some important toolkits are available for Neural Networks? But machine learning is not neural networks... you can do it with NNs, but there are so many other algorithms... I'm really surprise of this kind of posts in hacker news. I thought the audience here has other experiences.

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6 comments · 3 top-level

tinco3y ago· 2 in thread

That's literally the only one that didn't shock me. What universe do you live in where machine learning algorithms aren't tied together with Python? And what industry where machine learning is not mainly neural networks?

f1shyOP3y ago

In the company I work most of it is done in matlab for "putting together" then goes to C++. Again not neural networks. I'm saying all the other machine learning. Maybe rare case.

p1esk3y ago

What kind of machine learning does your company do? It's probably something simple, because for anything complicated, like computer vision, speech recognition, any non-trivial NLP, and large scale recommender systems you do need neural networks.

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plonk3y ago· 1 in thread

Python is the main language for PyTorch and TensorFlow, there are few ML frameworks more complete than Scikit-learn, I'm not aware of an equivalent to NumPy in other languages, and this list is probably missing other things I don't use.

What's the alternative for quick ML prototyping?

didibus3y ago

R, Matlab, Julia are some common alternatives.

Java/Scala I've also seen, specifically things around Spark ML, and Spark compute.

That said, Python is definitely the most common nowadays I'd say.

jandrewrogers3y ago

Python for machine learning is a coincidence of history.

Python is the traditional scripting language for high-performance computing (HPC) going back a very long time, as a wrapper for highly optimized and scalable C libraries. Python on supercomputers wasn't originally used for machine learning but it naturally included support for excellent linear algebra libraries, etc for various types of large-scale modeling. When machine learning first became trendy, data scientists that wanted access to mature library implementations of critical algorithms that worked very well at large scales were mostly limited to C/C++ or Python wrappers of that C/C++. Naturally, they chose Python for the same reason Python was already being used in HPC -- ease of use.

By virtue of its use in supercomputing, Python had uniquely strong support for many types of machine learning before there was a demand for machine learning. If HPC had used some other popular scripting language instead of Python, we'd probably be using that for machine learning right now.

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