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Deep Learning with Python by Francois Chollet

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Appendix A. Installing Keras and its dependencies on Ubuntu

The process of setting up a deep-learning workstation is fairly involved and consists of the following steps, which this appendix will cover in detail:

  1. Install the Python scientific suite—Numpy and SciPy—and make sure you have a Basic Linear Algebra Subprogram (BLAS) library installed so your models run fast on CPU.
  2. Install two extras packages that come in handy when using Keras: HDF5 (for saving large neural-network files) and Graphviz (for visualizing neural--network architectures).
  3. Make sure your GPU can run deep-learning code, by installing CUDA drivers and cuDNN.
  4. Install a backend for Keras: TensorFlow, CNTK, or Theano.
  5. Install Keras.

It may seem like a daunting process. In fact, ...

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