python. It contains the example code and solutions to the exercises in my O'Reilly book [Hands-on Machine Learning with Scikit-Learn and TensorFlow](http://shop.oreilly.com/product/0636920052289.do):
* note: [github.com's notebook viewer](https://github.com/ageron/handson-ml/blob/master/index.ipynb) also works but it is slower and the math formulas are not displayed correctly
Obviously, you will need [git](https://git-scm.com/) and [python](https://www.python.org/downloads/) (python 3 is recommended, but python 2 should work as well).
If you want to go through chapter 16 on Reinforcement Learning, you will need to [install OpenAI gym](https://gym.openai.com/docs) and its dependencies for Atari simulations.
This should start the Jupyter server locally, and open your browser. If your browser does not open automatically, visit [localhost:8888](http://localhost:8888/tree). Click on `index.ipynb` to get started. You can visit [http://localhost:8888/nbextensions](http://localhost:8888/nbextensions) to activate and configure Jupyter extensions.