Free TensorFlow 1.x Deep Learning Cookbook

Bestselling 536 page TensorFlow Deep Learning guide

In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow.

What You Will Learn

  • Install TensorFlow and use it for CPU and GPU operations
  • Implement DNNs and apply them to solve different AI-driven problems.
  • Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code.
  • Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box.
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