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Deep Learning Essentials

You're reading from   Deep Learning Essentials Your hands-on guide to the fundamentals of deep learning and neural network modeling

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781785880360
Length 284 pages
Edition 1st Edition
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Authors (3):
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Wei Di Wei Di
Author Profile Icon Wei Di
Wei Di
Anurag Bhardwaj Anurag Bhardwaj
Author Profile Icon Anurag Bhardwaj
Anurag Bhardwaj
Jianing Wei Jianing Wei
Author Profile Icon Jianing Wei
Jianing Wei
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Toc

Table of Contents (12) Chapters Close

Preface 1. Why Deep Learning? 2. Getting Yourself Ready for Deep Learning FREE CHAPTER 3. Getting Started with Neural Networks 4. Deep Learning in Computer Vision 5. NLP - Vector Representation 6. Advanced Natural Language Processing 7. Multimodality 8. Deep Reinforcement Learning 9. Deep Learning Hacks 10. Deep Learning Trends 11. Other Books You May Enjoy

Summary

In this chapter, we introduced concepts of reinforcement learning and how they are different from traditional supervised learning techniques. We described the core ideas behind RL, as well as basic modules such as Q-learning and policy learning that characterize any reinforcement learning technique today. We also presented deep learning-based advances to traditional RL techniques in form of DRL. We illustrated various different network architectures for DRL and discussed their relative merits. Finally, we sketched the core implementation of a few reinforcement learning tasks as applied to some popular computer-based games.

In next chapter, we will look at some of the practical tips and tricks used while implementing deep learning models in real world applications.

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