Tensortrade

# [TensorTrade: Trade Efficiently with Reinforcement Learning](https://towardsdatascience.com/trade-smarter-w-reinforcement-learning-a5e91163f315?source=friends_link&sk=ea3afd0a305141eb9147be4718826dfb)

[](https://travis-ci.org/notadamking/tensortrade) [](https://tensortrade.org) [](http://www.apache.org/licenses/LICENSE-2.0) [](https://discord.gg/ZZ7BGWh) [](https://www.python.org/downloads/release/python-360/)

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TensorTrade is an open source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning. The framework focuses on being highly composable and extensible, to allow the system to scale from simple trading strategies on a single CPU, to complex investment strategies run on a distribution of HPC machines.

Under the hood, the framework uses many of the APIs from existing machine learning libraries to maintain high quality data pipelines and learning models. One of the main goals of TensorTrade is to enable fast experimentation with algorithmic trading strategies, by leveraging the existing tools and pipelines provided by `numpy`, `pandas`, `gym`, `keras`, and `tensorflow`.

Every piece of the framework is split up into re-usable components, allowing you to take advantage of the general use components built by the community, while keeping your proprietary features private. The aim is to simplify the process of testing and deploying