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Learn TensorFlow 2.0

Implement Machine Learning and Deep Learning Models with Python

  • Pramod Singh
  • Avinash Manure
Book

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Pramod Singh, Avinash Manure
    Pages 1-24
  3. Pramod Singh, Avinash Manure
    Pages 25-52
  4. Pramod Singh, Avinash Manure
    Pages 53-74
  5. Pramod Singh, Avinash Manure
    Pages 75-106
  6. Pramod Singh, Avinash Manure
    Pages 107-129
  7. Pramod Singh, Avinash Manure
    Pages 131-159
  8. Back Matter
    Pages 161-164

About this book

Introduction

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. 

The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. 

You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways.

You will:
  • Review the new features of TensorFlow 2.0
  • Use TensorFlow 2.0 to build machine learning and deep learning models 
  • Perform sequence predictions using TensorFlow 2.0
  • Deploy TensorFlow 2.0 models with practical examples

Keywords

Machine Learning Deep Learning TensorFlow 2.0 Python Supervised Learning Neural Networks Generative Adversarial Networks

Authors and affiliations

  • Pramod Singh
    • 1
  • Avinash Manure
    • 2
  1. 1.BangaloreIndia
  2. 2.BangaloreIndia

Bibliographic information