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TensorFlow Machine Learning Cookbook

You're reading from TensorFlow Machine Learning Cookbook Over 60 recipes to build intelligent machine learning systems with the power of Python

Product type Paperback

Published in Aug 2018

Publisher Packt

ISBN-13 9781789131680

Length 422 pages

Edition 2nd Edition

Languages

Python

Tools

TensorFlow

Concepts

Machine Learning

Authors (2):

Nick McClure

Sujit Pal

View More author details

Table of Contents (19) Chapters

Title Page

Copyright and Credits

Dedication

Packt Upsell

Contributors

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

1. Other Books You May Enjoy

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Index

Using TensorFlow with Keras

TensorFlow is great for the flexibility and power it provides to the programmer. A drawback of this is that prototyping models, and iterating through various tests can be cumbersome for the programmer. Keras is a wrapper for deep learning libraries that makes it simpler to deal with various aspects of the model and make the programming easier. Here, we choose to use Keras on top of TensorFlow. In fact, using Keras with the TensorFlow backend is so popular, that there is a Keras library within TensorFlow. For this recipe, we will be using that TensorFlow library to do a fully connected neural network and a simple CNN image network on the MNIST dataset.

Getting ready

For this recipe, we will use the Keras functions that reside inside TensorFlow already. Keras (https://keras.io/) is already a separate python library which you can install. If you choose to go for the pure Keras route, you will have to choose a backend for Keras (like TensorFlow).

In this recipe we...

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Authors (2)

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.

See other products by Nick McClure

Sujit Pal

Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.

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