My solutions to the Machine Learning for Trading course exercises.
| assess_learners | ||
| crypto_eval | ||
| defeat_learners | ||
| manual_strategy | ||
| marketsim | ||
| martingale | ||
| optimize_something | ||
| playground | ||
| qlearning_robot | ||
| strategy_evaluation | ||
| zips | ||
| .gitignore | ||
| LICENSE | ||
| README.md | ||
| util.py | ||
ML4T
This is my solution to the ML4T course exercises. The main page for the course is here. The page contains a link to the assignments. There are eight projects in total. The summer 2020 page is here.
To set up the environment I have installed the following packages on my Linux Manjaro based system.
sudo pacman -S python-pandas --asdeps python-pandas-datareader python-numexpr \
python-bottleneck python-jinja python-scipy python-matplotlib \
python-numpy
I am also using mplfinance to plot candlestick-charts. You can install mplfinance via pip and find the tutorial here.
pip install mplfinance --user
I have included the archived version of the exercise. To extract them run the
following command. The -n flag makes unzip never overwrite existing files.
unzip -n zips/*.zip -d ./