TensorFlow 2.0 New Features [Video]

More Information
  • Focus mainly on the new features of TensorFlow 2.0 launched in Jan 2019.
  • Easy model building with TensorFlow and eager execution.
  • Robust model deployment in production on any platform.
  • Powerful experimentation for research.
  • Simplify your API by cleaning up deprecated APIs and reducing duplication.

TensorFlow is a popular and widely-adopted open-source Machine Learning library. It is Python-friendly and used in various AI areas such as deep learning, numeric computation, and large-scale Machine Learning. The newest version of TensorFlow includes major highlights such as improved eager execution, improved compatibility, support for major platforms and languages, and more; it also removes deprecated APIs. The new features will make TensorFlow easier to learn and apply.

In this course, you will cover all of the new features that have been introduced in TensorFlow 2.0 especially the major highlight including Eager Execution and more. You will learn how to make the best use of these features and how it improves and simplifies the way you use TensorFlow.

By the end of the course, you will have an understanding of the new features introduced in TensorFlow 2.0 and will be able to apply them in your work.

Style and Approach

This is an introductory course specially designed for programmers who are already working with the older version of TensorFlow and want to explore the new features in TensorFlow 2.0. Every module includes an illustration to help you understand concepts in depth and execute them in real-world case studies.

  • New features and functionality explained simply and easily via videos.
  • Code demos and examples help you understand how the new features work
  • Understand the differences between TensorFlow 1.x and 2.0, and how they're compatible
Course Length 1 hour 29 minutes
ISBN 9781789957198
Date Of Publication 28 Feb 2019


Radhika Datar

Radhika Datar has more than 5 years' experience in software development and content writing. She is well versed in frameworks such as Python, PHP, and Java, and regularly provides training on them. She has been working with Educba and Eduonix as a training consultant since June 2016, while also working as a freelance academic writer in data science and data analytics. She obtained her master's degree from the Symbiosis Institute of Computer Studies and Research and her bachelor's degree from K. J. Somaiya College of Science and Commerce.