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Deep Learning with TensorFlow. - Second Edition

You're reading from Deep Learning with TensorFlow. - Second Edition

Product type Book

Published in Mar 2018

Publisher Packt

ISBN-13 9781788831109

Pages 484 pages

Edition 2nd Edition

Languages

Concepts

Authors (2):

Giancarlo Zaccone

Md. Rezaul Karim

View More author details

Table of Contents (15) Chapters

Deep Learning with TensorFlow - Second Edition

Contributors

Preface

Other Books You May Enjoy

1. Getting Started with Deep Learning

2. A First Look at TensorFlow

3. Feed-Forward Neural Networks with TensorFlow

4. Convolutional Neural Networks

5. Optimizing TensorFlow Autoencoders

6. Recurrent Neural Networks

7. Heterogeneous and Distributed Computing

8. Advanced TensorFlow Programming

9. Recommendation Systems Using Factorization Machines

10. Reinforcement Learning

Index

Summary

In this chapter, we had a quick look at two fundamentals topics related to optimizing the computation of DNNs.

The first topic explained how to use GPUs and TensorFlow to implement DNNs. They are structured in a very uniform manner so that, at each layer of the network, thousands of identical artificial neurons perform the same computation. Hence, the architecture of a DNN fits quite well with the kinds of computation that a GPU can efficiently perform.

The second topic introduced distributed computing. This was initially used to perform very complex calculations that could not be completed by a single machine. Likewise, analyzing large amounts of data quickly by splitting this task among different nodes appears to be the best strategy when faced with such a big challenge.

At the same time, DL problems can be exploited using distributed computing. DL computations can be divided into multiple activities (tasks); each of them will be given a fraction of data and will return a result that...

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Authors (2)

Giancarlo Zaccone

Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems. Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing. Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).

See other products by Giancarlo Zaccone

Md. Rezaul Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

See other products by Md. Rezaul Karim

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