Updated Solutions and Implementations for Standford's CS229 Machine Learning
Caroline Wang - Eitan Joseph
Taught by Prof. Andrew Ng
This repository contains all the coursework for Prof. Andrew Ng's CS229 ML class separated into folders for different problem sets. For each problem set there are fully detailed derivations and corrected solutions extensively typed out in LaTeX.
Alongside the derivations there are also example algorithm implementations in MATLAB for Independent Component Analysis, Principle Component Analysis, Q-learning, K-means Clustering, L1 Regularization for Least Squares, and Locally Weighted Logistic Regression.
Each problem set contains a Latex file with extension .tex and some other file for hands-on application such as MATLAB files (extension .m).
- To use the MATLAB files you can simply import the entire project directory into MATLAB and run the code there.
- To view the a .tex file just open it in some Latex interpreter. All .tex files were written in Overleaf.
Note: Many of the problem set solutions throughout the course needed to be corrected - there are some incorrect solutions/typos in the actual coursework. There are notes on the specific corrections throughout the repository with detailed derivations in the LaTeX documents.
If you have any questions you can shoot either of us an email at