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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 8. Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are responsible for the major breakthroughs in image recognition made in the past few years. In this chapter we will cover:

Implementing a Simpler CNN
Implementing an Advanced CNN
Retraining Existing CNN models
Applying Stylenet/Neural-Style
Implementing DeepDream

As a reminder, the reader may find all of the code for this chapter available online here: https://github.com/nfmcclure/tensorflow_cookbook.

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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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