r/learnmachinelearning • u/Nervous-Employ8202 • 12h ago

Title: Looking for good resources to learn machine learning

Hello all,

I have been studying programming for one year already, and lately, I have got more and more interested in machine learning.

I have created several projects, for example, pathfinding bots and classifiers, and now I want to find some materials which could explain what is happening **under the hood** in frameworks like scikit-learn.

I want to learn how those algorithms work and what the math behind them is rather than learn how to use those functions from a framework.

All sorts of materials are welcome – books, courses, slides, PDFs or anything else.

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u/OleksandrAkm 10h ago

Here’s a GitHub repository where you will find code that builds ML algorithms with just NumPy, mirroring what happens under the hood in Scikit-learn: https://github.com/ml-from-scratch-book/code

It’s a companion repo to the book I recently published, which is exactly what you are looking for.

Feel free to ask any questions

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u/nian2326076 2h ago

If you're trying to get into the math and algorithms behind machine learning, check out "Pattern Recognition and Machine Learning" by Christopher M. Bishop. It's a bit dense but really solid on the math side. For practical stuff, "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron is super useful. For free resources, Andrew Ng's Machine Learning course on Coursera is in-depth but easy to follow. If you prefer video lectures, MIT's OpenCourseWare has some good ones on ML. Jump in, and don't worry if it's tough at first. It gets easier with practice!