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TensorFlow Machine Learning Cookbook

You're reading from TensorFlow Machine Learning Cookbook Over 60 practical recipes to help you master Google's TensorFlow machine learning library

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781786462169

Length 370 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Author (1):

Nick McClure

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with TensorFlow FREE CHAPTER

2. The TensorFlow Way

3. Linear Regression

4. Support Vector Machines

5. Nearest Neighbor Methods

6. Neural Networks

7. Natural Language Processing

8. Convolutional Neural Networks

9. Recurrent Neural Networks

10. Taking TensorFlow to Production

11. More with TensorFlow

Index

Chapter 2. The TensorFlow Way

In this chapter, we will introduce the key components of how TensorFlow operates. Then we will tie it together to create a simple classifier and evaluate the outcomes. By the end of the chapter you should have learned about the following:

Operations in a Computational Graph
Layering Nested Operations
Working with Multiple Layers
Implementing Loss Functions
Implementing Back Propagation
Working with Batch and Stochastic Training
Combining Everything Together
Evaluating Models

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Authors (1)

Nick McClure

Nick McClure

Nick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow Group and Caesar's Entertainment Corporation. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict and Saint John's University. He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence. Nick occasionally puts his thoughts and musings on his blog or through his Twitter account, @nfmcclure.

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