# Installation & Set-up To install and use ML-Agents, you need install Unity, clone this repository and install Python with additional dependencies. Each of the subsections below overviews each step, in addition to an experimental Docker set-up. ## Install **Unity 2017.1** or Later [Download](https://store.unity.com/download) and install Unity. If you would like to use our Docker set-up (introduced later), make sure to select the _Linux Build Support_ component when installing Unity.
## Clone the ml-agents Repository Once installed, you will want to clone the ML-Agents GitHub repository. git clone git@github.com:Unity-Technologies/ml-agents.git The `unity-environment` directory in this repository contains the Unity Assets to add to your projects. The `python` directory contains the training code. Both directories are located at the root of the repository. ## Install Python (with Dependencies) In order to use ML-Agents, you need Python 3 along with the dependencies listed in the [requirements file](../python/requirements.txt). Some of the primary dependencies include: - [TensorFlow](Background-TensorFlow.md) - [Jupyter](Background-Jupyter.md) ### Windows Users If you are a Windows user who is new to Python and TensorFlow, follow [this guide](https://unity3d.college/2017/10/25/machine-learning-in-unity3d-setting-up-the-environment-tensorflow-for-agentml-on-windows-10/) to set up your Python environment. ### Mac and Unix Users If your Python environment doesn't include `pip`, see these [instructions](https://packaging.python.org/guides/installing-using-linux-tools/#installing-pip-setuptools-wheel-with-linux-package-managers) on installing it. To install dependencies, go into the `python` subdirectory of the repository, and run from the command line: pip3 install . ## Docker-based Installation (Experimental) If you'd like to use Docker for ML-Agents, please follow [this guide](Using-Docker.md). ## Help If you run into any problems installing ML-Agents, [submit an issue](https://github.com/Unity-Technologies/ml-agents/issues) and make sure to cite relevant information on OS, Python version, and exact error message (whenever possible).