What's New in TensorFlow 2.0: Use the new and improved features of TensorFlow to enhance machine learning and deep learning (English Edition)

What's New in TensorFlow 2.0: Use the new and improved features of TensorFlow to enhance machine learning and deep learning (English Edition)

作者
Ajay Baranwal、Alizishaan Khatri、Tanish Baranwal
语言
英语
出版社
Packt Publishing 版次:1
出版日期
2019年8月12日
纸书页数
202页
电子书格式
epub,pdf,mobi,azw3,txt,fb2,djvu
文件大小
4905 KB
下载次数
1658
更新日期
2023-05-20
运行环境
PC/Windows/Linux/Mac/IOS/iPhone/iPad/iBooks/Kindle/Android/安卓/平板
内容简介

Get to grips with key structural changes in TensorFlow 2.0

Key Features

Explore TF Keras APIs and strategies to run GPUs, TPUs, and compatible APIs across the TensorFlow ecosystem

Learn and implement best practices for building data ingestion pipelines using TF 2.0 APIs

Migrate your existing code from TensorFlow 1.x to TensorFlow 2.0 seamlessly

Book Description

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.

What you will learn

Implement tf.keras APIs in TF 2.0 to build, train, and deploy production-grade models

Build models with Keras integration and eager execution

Explore distribution strategies to run models on GPUs and TPUs

Perform what-if analysis with TensorBoard across a variety of models

Discover Vision Kit, Voice Kit, and the Edge TPU for model deployments

Build complex input data pipelines for ingesting large training datasets

Who this book is for

If you’re a data scientist, machine learning practitioner, deep learning researcher, or AI enthusiast who wants to migrate code to TensorFlow 2.0 and explore the latest features of TensorFlow 2.0, this book is for you. Prior experience with TensorFlow and Python programming is necessary to understand the concepts covered in the book. Table of Contents

Getting Started with TensorFlow 2.0

Keras Default Integration and Eager Execution

Design and Construct Input Data Pipelines

Model Training and Use of Tensorboard

Model Inference Pipelines: Multi-platform Deployments

AIY Projects and TensorFlow Lite

Migrating from TensorFlow 1.x to 2.0

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