Machine Learning Notebooks ========================== [![Gitter](https://badges.gitter.im/ageron/ml-notebooks.svg)](https://gitter.im/ageron/ml-notebooks?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) This project aims at teaching you the fundamentals of Machine Learning in python. Simply open the [Jupyter](http://jupyter.org/) notebooks you are interested in: * using [Binder](http://mybinder.org/): [![Binder](http://mybinder.org/badge.svg)](http://mybinder.org/repo/ageron/ml-notebooks) * this let's you experiment with the code examples * or directly within github (start at [index.ipynb](https://github.com/ageron/ml-notebooks/blob/master/index.ipynb)) * or by cloning this repository and running Jupyter locally. * if you prefer this option, follow the installation instructions below. # Installation No installation is required, just click the *launch binder* button above, and you're good to go! But if you insist, here's how to install these notebooks on your system. Obviously, you will need [git](https://git-scm.com/) and [python](https://www.python.org/downloads/) (2 or 3). First, clone this repository: $ cd {your development directory} $ git clone https://github.com/ageron/ml-notebooks.git $ cd ml-notebooks If you want an isolated environment, you can use [virtualenv](https://virtualenv.readthedocs.org/en/latest/): $ virtualenv env $ source ./env/bin/activate There are different packages for TensorFlow, depending on your platform. Please edit `requirements.txt` using your favorite editor, and make sure only the right one for your platform is uncommented. Default is Python 2, Ubuntu/Linux 64-bits, CPU-only. Then install the required python packages using pip: $ pip install -r requirements.txt Finally, launch Jupyter: $ jupyter notebook This should start the Jupyter server locally, and open your browser. Click on `index.ipynb` to get started.