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My solutions to the Machine Learning for Trading course exercises.
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Felix Martin e577ce34d2 Add support for trading view data 2 years ago
assess_learners Finish report for project 3. 3 years ago
crypto_eval Add support for trading view data 2 years ago
defeat_learners Finish project 4 3 years ago
manual_strategy Fix picture link in project 6 report 3 years ago
marketsim Make marketsim support buying and selling via sign of shares 3 years ago
martingale Fix mistake in previous solution and finish report for project 1. 3 years ago
optimize_something Finish report for project 3. 3 years ago
playground Start with optimize something exercise. Also add a playground for testing candlestick plotting via mplfinance. 3 years ago
qlearning_robot Implement dyna-q to finish project 7 3 years ago
strategy_evaluation Finish project 8 and course! 3 years ago
zips Add template for project 8 3 years ago
.gitignore Add util because I cannot remember why I would ignore it 2 years ago
LICENSE Add readme and license. 3 years ago
README.md Add project 8 report to readme 3 years ago
util.py Add support for trading view data 2 years ago



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  \

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 ./