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Teaching an Agent to Trade using Reinforcement Learning

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Reinforcement_Trader

This is an experimental Reinforcement Learning based Bitcoin trader program.

Utils Folder

The utils folder consists of the functions that download data, pickle the data, get state information and decipher the action that the agent might be taking

Data Folder

This is where the data pickles are stored

Logs and Models Folder

The logs are where the logs from the Agent are stored. The Models folder is where the saved models are stored

Scripts Folder

The scripts folder has the implementation.ipynb which runs the Agent and kicks off the MDP and the learning process.

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Teaching an Agent to Trade using Reinforcement Learning

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