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Deep Learning with TensorFlow

You're reading from   Deep Learning with TensorFlow Explore neural networks with Python

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781786469786
Length 320 pages
Edition 1st Edition
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Authors (4):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Ahmed Menshawy Ahmed Menshawy
Author Profile Icon Ahmed Menshawy
Ahmed Menshawy
Giancarlo Zaccone Giancarlo Zaccone
Author Profile Icon Giancarlo Zaccone
Giancarlo Zaccone
Fabrizio Milo Fabrizio Milo
Author Profile Icon Fabrizio Milo
Fabrizio Milo
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Started with Deep Learning 2. First Look at TensorFlow FREE CHAPTER 3. Using TensorFlow on a Feed-Forward Neural Network 4. TensorFlow on a Convolutional Neural Network 5. Optimizing TensorFlow Autoencoders 6. Recurrent Neural Networks 7. GPU Computing 8. Advanced TensorFlow Programming 9. Advanced Multimedia Programming with TensorFlow 10. Reinforcement Learning

What you need for this book

All the examples have been implemented using Python version 2.7 (and 3.5) on an Ubuntu Linux 64 bit including the TensorFlow library version 1.0.1. However, all the source codes that are shown in the book are Python 2.7 compatible. Further, source codes for Python 3.5 compatible can be downloaded from the Packt repository. Source codes for Python 3.5+ compatible can be downloaded from the Packt repository.

You will also need the following Python modules (preferably the latest version):

  • Pip
  • Bazel
  • Matplotlib
  • NumPy
  • Pandas
  • mnist_data

For chapters 8, 9 and 10, you will need the following frameworks too:

  • Keras
  • XLA
  • Pretty Tensor
  • TFLearn
  • OpenAI gym

Most importantly, GPU-enabled version of TensorFlow has several requirements such as 64-bit Linux, Python 2.7 (or 3.3+ for Python 3), NVIDIA CUDA® 7.5 (CUDA 8.0 required for Pascal GPUs) and NVIDIA cuDNN v4.0 (minimum) or v5.1 (recommended). More specifically, the current implementation of TensorFlow supports GPU computing with NVIDIA toolkits, drivers and software only.

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