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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

Deep Learning in Computer Vision

In the previous chapter, we covered the basics of a neural network and how it is trained and applied for solving a specific artificial intelligence (AI) task. As outlined in the chapter, one of the most popular deep learning models that are broadly used in the field of computer vision is a convolutional neural network, also known as a CNN. This chapter aims to cover CNNs in more detail. We will go over core concepts that are essential to the working of a CNN, and how they can be used to solve real-world computer vision problems. We will specifically answer the following questions:

  • How did CNNs originate and what is their historical significance?
  • What core concepts form the basis for understanding CNNs?
  • What are some of the popular CNN architectures in use today?
  • How do you implement basic functionality of a CNN using TensorFlow?
  • How do you fine...
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