What’s New in TensorFlow 2.0: Use the new and improved features of TensorFlow to enhance machine learning and deep learning 1st Edition [NulledPremium]

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Book details
Format: epub
File Size: 2.40 MB
Print Length: 202 pages
Publisher: Packt Publishing; 1 edition (12 August 2019)
Sold by: Amazon Asia-Pacific Holdings Private Limited
Language: English
ASIN: B07VWGN8NB

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.

About this Book

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
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