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Hands-On Deep Learning with TensorFlow

You're reading from Hands-On Deep Learning with TensorFlow Uncover what is underneath your data!

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787282773

Length 174 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Deep Learning

Author (1):

Dan Van Boxel

View More author details

Table of Contents (7) Chapters

Preface

1. Getting Started

2. Deep Neural Networks FREE CHAPTER

3. Convolutional Neural Networks

4. Introducing Recurrent Neural Networks

5. Wrapping Up

Index

Summary

In this chapter, we reviewed how we climbed from a humble logistic regression model to flying high with a deep convolutional neural network to classify fonts. We also discussed the future of TensorFlow. We finally recalled our TensorFlow models for font classification, reviewing their accuracy. We also took some time to discuss where TensorFlow is headed. Congratulations! You're now well-versed in TensorFlow. You've applied it to multiple research problems and models in this series, and learned how it's widely applicable.

The next step is to deploy TensorFlow in one of your own projects. Happy modeling!

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Authors (1)

Dan Van Boxel

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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