/stanford-cs229

🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford

Primary LanguageJupyter Notebook

Introduction

This repo records my answers to all questions from the excercises of CS229 (Autumn 2017). http://cs229.stanford.edu/syllabus.html

I tried to record all details in Jupyter notebooks. If you see any mistake, please let me know by opening a new issue.

As for reinforcement learning, I've also implemented value iteration, policy iteration, SARSA, and Q-learning before in javascript for the gridworld at https://github.com/zyxue/rljs with a web demo at https://rljs.herokuapp.com/.

I find some of the homeworks in an earlier version (https://see.stanford.edu/Course/CS229) of this course interesting, so I chose to do some and placed the answers in the previous_cs229 fold.

Usage

For non-interactive visualization of the notebooks, you could either read them on github directly, or use http://nbviewer.jupyter.org/ for somewhat better quality.

If you'd also like to modify the notebooks without setting up a local server, you may give https://mybinder.org/ a try.

Development

Create virtual environment:

conda env create --prefix venv -f env-conda.yml

Start the server

jupyter notebook --no-browser --ip 0.0.0.0

Export virtual environment:

conda env export --prefix venv > env-conda.yml

About LaTeX

For interactive LaTeX editing, you could use https://www.codecogs.com/latex/eqneditor.php.