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Machine Learning Notebooks
==========================
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[![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)
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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:
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* using Binder: [![Binder ](http://mybinder.org/badge.svg )](http://mybinder.org/repo/ageron/ml-notebooks)
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* this let's you experiment with the code examples
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* or using [jupyter.org's notebook viewer ](http://nbviewer.jupyter.org/github/ageron/ml-notebooks/blob/master/index.ipynb )
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* note: [github.com's notebook viewer ](https://github.com/ageron/ml-notebooks/blob/master/index.ipynb ) also works but it is slower and the math formulas are not displayed correctly
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* or by cloning this repository and running Jupyter locally
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* if you prefer this option, follow the installation instructions below.
# Installation
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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.
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Obviously, you will need [git ](https://git-scm.com/ ) and [python ](https://www.python.org/downloads/ ) (2 or 3).
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First, clone this repository:
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$ cd {your development directory}
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$ 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
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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.
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Then install the required python packages using pip:
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$ pip install -r requirements.txt
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Finally, launch Jupyter:
$ jupyter notebook
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This should start the Jupyter server locally, and open your browser. Click on `index.ipynb` to get started.