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

Model Inference Pipelines - Multi-platform Deployments

What do you do after a model has been trained to perfection? Use it? If the answer is yes, then how do you use it? The answer you're looking for is inference. Simply put, the process of inference is what is needed to ensure that machine learning models can be used for serving the needs of actual users. Formally put, inference is the process of computing trained machine learning models efficiently to serve the user's needs. Inference can be performed on a variety of hardware types including servers, and end user devices such as phones and web browsers. As per user requirements, it can also be performed on different operating systems.

Previous chapters have focused on the process of how to build a model. This chapter will cover a detailed overview of the inference stage. First, you will cover a detailed...