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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 FREE CHAPTER

2. Deep Neural Networks

3. Convolutional Neural Networks

4. Introducing Recurrent Neural Networks

5. Wrapping Up

Index

The future of TensorFlow

In this section, we will observe how TensorFlow is changing, who is starting to use TensorFlow, and how you can make an impact contributing to it.

Since it was released in late 2015, TensorFlow has already seen several more releases:

The future of TensorFlow

TensorFlow is constantly being updated. Although it isn't an official Google product, it is also open source and hosted on GitHub. At the time of writing, TensorFlow is at release 1.2. The most recent release added distributed computing capabilities. These are beyond the scope of this book, but generally speaking, they allow computation across multiple GPUs on multiple machines for maximum parallelization. Under heavy development, more features are always just around the corner. TensorFlow is becoming more popular every day.

Several software companies have released machine learning frameworks recently, but TensorFlow stands out in adoption. Internally, Google is practicing what they preach. Their acclaimed DeepMind team has switched...

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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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