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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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SteveWang1992/handson-ml2

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Machine Learning Notebooks

Gitter

This project aims at teaching you the fundamentals of Machine Learning in python.

Simply open the Jupyter notebooks you are interested in:

  • using Binder: Binder
    • this let's you experiment with the code examples
  • or directly within github (start at 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 and python (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:

$ 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.

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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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