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What's New in TensorFlow 2.0

You're reading from   What's New in TensorFlow 2.0 Use the new and improved features of TensorFlow to enhance machine learning and deep learning

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838823856
Length 202 pages
Edition 1st Edition
Languages
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Authors (3):
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Tanish Baranwal Tanish Baranwal
Author Profile Icon Tanish Baranwal
Tanish Baranwal
Alizishaan Khatri Alizishaan Khatri
Author Profile Icon Alizishaan Khatri
Alizishaan Khatri
Ajay Baranwal Ajay Baranwal
Author Profile Icon Ajay Baranwal
Ajay Baranwal
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Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: TensorFlow 2.0 - Architecture and API Changes
2. Getting Started with TensorFlow 2.0 FREE CHAPTER 3. Keras Default Integration and Eager Execution 4. Section 2: TensorFlow 2.0 - Data and Model Training Pipelines
5. Designing and Constructing Input Data Pipelines 6. Model Training and Use of TensorBoard 7. Section 3: TensorFlow 2.0 - Model Inference and Deployment and AIY
8. Model Inference Pipelines - Multi-platform Deployments 9. AIY Projects and TensorFlow Lite 10. Section 4: TensorFlow 2.0 - Migration, Summary
11. Migrating From TensorFlow 1.x to 2.0 12. Other Books You May Enjoy

Preface

TensorFlow is one of the most popular machine learning frameworks, and its new version, TensorFlow 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 TensorFlow 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 the compatibility between TensorFlow 2.0 and TensorFlow 1.x and will be able to smoothly migrate to TensorFlow 2.0.

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