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You're reading from TensorFlow 2.0 Quick Start Guide Get up to speed with the newly introduced features of TensorFlow 2.0

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789530759

Length 196 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Author (1):

Tony Holdroyd

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Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to TensorFlow 2.00 Alpha

2. Introducing TensorFlow 2 FREE CHAPTER

3. Keras, a High-Level API for TensorFlow 2

4. ANN Technologies Using TensorFlow 2

5. Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha

6. Supervised Machine Learning Using TensorFlow 2

7. Unsupervised Learning Using TensorFlow 2

8. Section 3: Neural Network Applications of TensorFlow 2.00 Alpha

9. Recognizing Images with TensorFlow 2

10. Neural Style Transfer Using TensorFlow 2

11. Recurrent Neural Networks Using TensorFlow 2

12. TensorFlow Estimators and TensorFlow Hub

13. Converting from tf1.12 to tf2

14. Other Books You May Enjoy

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Section 1: Introduction to TensorFlow 2.00 Alpha

In this section, we will introduce TensorFlow 2.00 alpha. We will begin with an overview of the major features of this machine learning ecosystem and see some examples of its use. We will then introduce TensorFlow's high-level Keras API. We will end the section with an investigation of artificial neural network technologies and techniques.

This section contains the following chapters:

Chapter 1, Introducing TensorFlow 2
Chapter 2, Keras, a High-Level API for TensorFlow 2
Chapter 3, ANN Technologies Using TensorFlow 2

The rest of the chapter is locked

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Authors (1)

Holdroyd

Tony Holdroyd's first degree, from Durham University, was in maths and physics. He also has technical qualifications, including MCSD, MCSD.net, and SCJP. He holds an MSc in computer science from London University. He was a senior lecturer in computer science and maths in further education, designing and delivering programming courses in many languages, including C, C+, Java, C#, and SQL. His passion for neural networks stems from research he did for his MSc thesis. He has developed numerous machine learning, neural network, and deep learning applications, and has advised in the media industry on deep learning as applied to image and music processing. Tony lives in Gravesend, Kent, UK, with his wife, Sue McCreeth, who is a renowned musician.

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