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We present here the capstone project report for the Machine Learning Nanodegree from Udacity. We have borrowed the Deep Q Learning algorithm originally developed by Google Deepmind and adapted to play the financial trading game. The agent developed was trained to learn trading Bitcoin in our simulated BitMEX exchange

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Udacity Machine Learning Nanodegree Capstone Project

Algorithmic trading using Deep-Q Reinforcement Learning methods

This is the final graduation capstone project were I explain the approach to develop a Reinforcement Learning agent designed to learn to trade Bitcoin.

Find also the link to the companion repository that contains the code for the deep-q trading agent.

I have used a dataset consisting of OHLCV prices from BitMEX, quite a traditional approach. As order book historical dataset is available from sites like algorithmic.ch, it would be great to see how does the model perform trying to predict bitcoin prices from the order book perspective.

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We present here the capstone project report for the Machine Learning Nanodegree from Udacity. We have borrowed the Deep Q Learning algorithm originally developed by Google Deepmind and adapted to play the financial trading game. The agent developed was trained to learn trading Bitcoin in our simulated BitMEX exchange

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