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, where I wrote detailed lecture notes for all 10 chapters. These notes cover everything from linear regression to reinforcement learning, ensuring even beginners can follow along without getting lost.

The notes are written in LaTeX and auto-compiled to PDF via GitHub Actions whenever I push an update, keeping them always up-to-date. They’re available at this [GitHub repository](https://github.com/TruongDat05/machine-learning-notes-and-code).

**Takeaways:**
– **Accessible Knowledge:** Andrew Ng’s course is now more accessible with these comprehensive notes.
– **Self-Paced Learning:** Ideal for those who want to learn ML independently, without the need for a live course.
– **Educational Resource:** A valuable resource for students and professionals looking to deepen their understanding of machine learning.

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