•1 min read•from Machine Learning
All fundamental knowledge in ML Course by Andrew NG that I noted and create into a repo github [R]
![All fundamental knowledge in ML Course by Andrew NG that I noted and create into a repo github [R]](/_next/image?url=https%3A%2F%2Fpreview.redd.it%2Fmikhasjiq32h1.png%3Fwidth%3D140%26height%3D140%26crop%3D1%3A1%2Csmart%26auto%3Dwebp%26s%3D093f471efd959687e728246ef987377f43b2a875&w=3840&q=75)
![All fundamental knowledge in ML Course by Andrew NG that I noted and create into a repo github [R]](https://preview.redd.it/mikhasjiq32h1.png?width=140&height=140&crop=1:1,smart&auto=webp&s=093f471efd959687e728246ef987377f43b2a875 "All fundamental knowledge in ML Course by Andrew NG that I noted and create into a repo github [R]") | 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 [link] [comments] |
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