Learning TensorFlow 2.0 [Video]

More Information
  • A comprehensive guide to the new features in TensorFlow 2.0 (and a recap of TF1.0 for newcomers)
  • How to utilize the special way of writing code using the Graph Mode and Eager Execution
  • Learn complicated concepts such as computation graphs, sessions, placeholders using demo code
  • Understand how to use Eager Execution in an effective manner
  • Learn about the upgrade tool to make your existing TF1.0 code compatible with TF2.0
  • Learn how image recognition works; how it is implemented using Convolutional Neural Networks (CNN); and what’s new in TF2.0
  • How to apply transfer learning and train your network faster with less data
  • Learn about Recurrent Neural Networks (RNN) and how they are improved in TF2.0

TensorFlow is one of the most popular Google deep learning libraries and has become the industry standard for building AI applications. With the new release of TensorFlow 2.0, its many powerful new features speed up the development process.

In this course, we talk about all these new features and paradigms. With our TensorFlow course, you'll master TensorFlow concepts, learn to apply algorithms, and build artificial neural networks—all of these are crucial to deep learning and Artificial Intelligence. After you've mastered the new features in TensorFlow 2.0, you'll be able to rapidly build prototypes and move them to production.

By the end of this course, you will be able to implement models effectively, easily, and confidently with TensorFlow 2.0.

All the code and supporting files for this course are available on GitHub at https://github.com/PacktPublishing/Learning-TensorFlow-2.0

  • The new features and functionality are explained in simple, easy-to-understand videos
  • Several code demos and examples help you understand how the new features work
  • Ready-to-run code files are provided in the form of Jupyter Notebook files for hands-on practice
Course Length 4 hours 8 minutes
ISBN 9781789951370
Date Of Publication 30 Apr 2019