So I wanted to get into ML using Python recently and I was wondering about which ML library I should learn as a ML beginner first. I’ve been using Python for a few years now.
For more “traditional” or “statistical” modeling (not NN) 100% start with sklearn. It has a plethora of algorithms, and their docs read like a book. You can learn a whole bunch of new methods and techniques from there too. In tandum, you should familiarize yourself with matplotlib, which is the plotting library it uses under the hood (and is by far the most popular plotting library.)
For deep learning, I’d say PyTorch? Tensorflow used to be standard but its fallen out of favor compared to PyTorch. I don’t use either so I’m nit sure.
Sklearn for most of the data handling, pytorch for the model. They’re designed to be useable together.
It’s been a while since I last looked into those.
If you aren’t looking for neural networks I found sklearn to be quite capable and easy to understand.
I also tried tensorflow and pytorch a couple times (not enough to get really proficient in them) and I think I found pytorch the hardest to wrap my head around. It’s been quite a while though so maybe it’s better to listen to others with more experience in that regard.
What is ML?
Microwaveable Legos
Machine Learning
Maybe find some code to look at on the HuggingFace hub page? HuggingFace libraries or PyTorch are likely to give you really good learning opportunities and examples. Just keep an eye out for timestamps of articles or version numbers. And of course use venv/conda/… to not mess up your version when trying out different things 😉
Sklearn has those built in graphs and chart displays
