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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 have introduced the high-level concept of deep learning and AI in general. We talked about the history of deep learning, the up and downs, and its recent rise. From there, we dived deeper to discuss the differences between shallow algorithms and deep algorithms. We specifically discussed the two aspects of understanding deep learning: the neural point view and feature representation learning point of view. We then gave several successful applications across various fields. In the end, we talked about challenges that deep learning still faces and the potential future for machine-based AI.

In the next chapter, we will help you set up the development environment and get our hands dirty.

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