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