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Hands-On Deep Learning with TensorFlow

You're reading from Hands-On Deep Learning with TensorFlow

Product type Book

Published in Jul 2017

Publisher Packt

ISBN-13 9781787282773

Pages 174 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Dan Van Boxel

Table of Contents (12) Chapters

Hands-On Deep Learning with TensorFlow

Credits

About the Author

www.PacktPub.com

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Preface

1. Getting Started

2. Deep Neural Networks

3. Convolutional Neural Networks

4. Introducing Recurrent Neural Networks

5. Wrapping Up

Index

Summary

You learned a lot in this chapter, going from simply understanding RNNs to implementing them in a new TensorFlow model. We also looked at a simple interface to TensorFlow called TensorFlow Learn. We also walked through DNNs, and understood CNNs and extracting weights in detail.

In the next chapter, we will wrap up our look at TensorFlow, looking at how far we've come and where you can go from here.

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Authors (1)

Dan Van Boxel

Dan Van Boxel is a data scientist and machine learning engineer with over 10 years of experience. He is most well-known for Dan Does Data, a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research articles and presented findings at the Transportation Research Board and other academic journals.

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