Overview
Implementation is kept simple and as close as possible to the algorithm discussed in the paper, for learning purposes.
Introduction
Generally, Reinforcement Learning is a family of machine learning techniques that allow us to create intelligent agents that learn from the environment by interacting with it, as they learn an optimal policy by trial and error. This is especially useful in many real world tasks where supervised learning might not be the best approach due to various reasons like nature of task itself, lack of appropriate labelled data, etc.
Results
You can obtain similar visualizations of your model evaluations using the notebook provided.
Data
You can download Historical Financial data through the relevant code
Getting Started
In order to use this project, you'll need to install the required python packages