Book Image

What's New in TensorFlow 2.0

By : Ajay Baranwal, Alizishaan Khatri, Tanish Baranwal
Book Image

What's New in TensorFlow 2.0

By: Ajay Baranwal, Alizishaan Khatri, Tanish Baranwal

Overview of this book

TensorFlow is an end-to-end machine learning platform for experts as well as beginners, and its new version, TensorFlow 2.0 (TF 2.0), improves its simplicity and ease of use. This book will help you understand and utilize the latest TensorFlow features. What's New in TensorFlow 2.0 starts by focusing on advanced concepts such as the new TensorFlow Keras APIs, eager execution, and efficient distribution strategies that help you to run your machine learning models on multiple GPUs and TPUs. The book then takes you through the process of building data ingestion and training pipelines, and it provides recommendations and best practices for feeding data to models created using the new tf.keras API. You'll explore the process of building an inference pipeline using TF Serving and other multi-platform deployments before moving on to explore the newly released AIY, which is essentially do-it-yourself AI. This book delves into the core APIs to help you build unified convolutional and recurrent layers and use TensorBoard to visualize deep learning models using what-if analysis. By the end of the book, you'll have learned about compatibility between TF 2.0 and TF 1.x and be able to migrate to TF 2.0 smoothly.
Table of Contents (13 chapters)
Title Page

Technical requirements

You should know about standard data formats such as CSV files, images (PNG and JPG), and ASCII text formats. Needless to say, most of the chapters in this book assume that you know about basic machine learning concepts, Python programming, the numpy Python module, and that you have used TensorFlow to create some machine learning models. Though it's not required, having familiarity with tf.data APIs from TensorFlow 1.x (TF 1.x) versions will be helpful. Even if you don't have prior knowledge of tf.data APIs, you should find this chapter self-sufficient to learn about them.

Some of the topics in this chapter require Python modules such as argparse and tqdm, which are listed on this book's GitHub repository. The code for this chapter is available at https://github.com/PacktPublishing/What-s-New-in-TensorFlow-2.0/tree/master...