All fundamental knowledge in ML Course by Andrew NG that I noted and create into a repo github [R]

Reddit r/MachineLearning Tools

Summary

A user shares a GitHub repository containing detailed lecture notes for all 10 chapters of Andrew Ng's Machine Learning Specialization, written in LaTeX and automatically compiled to PDF.

https://preview.redd.it/mikhasjiq32h1.png?width=572&format=png&auto=webp&s=4c053200dbd9852bebf083550e2144b31579d497 https://preview.redd.it/bay5r3njq32h1.png?width=575&format=png&auto=webp&s=2823db3d6bc534ef00330528a200cba2aca1c5d3 https://preview.redd.it/dm40ntdkq32h1.png?width=575&format=png&auto=webp&s=703beb099eb6e16d2789ac230ebe77de51f07d7a https://preview.redd.it/eubucz2lq32h1.png?width=575&format=png&auto=webp&s=fb5a8d9a7154396087da33487674cda785d2a62a https://preview.redd.it/0xo3t83nq32h1.png?width=586&format=png&auto=webp&s=a569ae89c44953a5bc9aff6fbb37d25759109dd1 I've just finished the Machine Learning Specialization by Andrew Ng , and as I was going through it, I ended up writing detailed lecture notes for all 10 chapters — everything from linear regression all the way to reinforcement learning. I put a lot of effort into making these notes as clear and friendly as possible, so even if you're completely new to ML, you should be able to follow along without getting lost. The notes are written in LaTeX and auto-compiled to PDF via GitHub Actions whenever I push an update, so the PDF is always up to date. 🔗 GitHub: [https://github.com/TruongDat05/machine-learning-notes-and-code](https://github.com/TruongDat05/machine-learning-notes-and-code)
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