ankile / reinforcement-trading

Deep Q-learning/TCN-based naive trading bot in the crypto markets created as part of the course NEURO140 at Harvard

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Deep Q-Learning for Trading Cryptocurrencies

Running in colab

Just open one of the training notebooks or the testing notebook and press the "Open in Colab"-button at the top to launch the code in Colab.

Running locally

Clone this repo to local computer. cd into the repo-folder.

Create virtualenv

virtualenv .env -p <path to python binary to use> e.g. virtualenv .env -p python3

Enter virtualenv

source .env/bin/activate

Install requirements

pip install -r requirements.txt --no-deps

Run the training file (and/or do desired changes before starting training)

python train_agent.py

Notes

The testing file is only available in a colab format

About

Deep Q-learning/TCN-based naive trading bot in the crypto markets created as part of the course NEURO140 at Harvard

License:MIT License


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Language:Jupyter Notebook 94.5%Language:Python 5.5%