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Hands-On Deep Learning with R

You're reading from   Hands-On Deep Learning with R A practical guide to designing, building, and improving neural network models using R

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781788996839
Length 330 pages
Edition 1st Edition
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Authors (2):
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Rodger Devine Rodger Devine
Author Profile Icon Rodger Devine
Rodger Devine
Michael Pawlus Michael Pawlus
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Michael Pawlus
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Deep Learning Basics
2. Machine Learning Basics FREE CHAPTER 3. Setting Up R for Deep Learning 4. Artificial Neural Networks 5. Section 2: Deep Learning Applications
6. CNNs for Image Recognition 7. Multilayer Perceptron for Signal Detection 8. Neural Collaborative Filtering Using Embeddings 9. Deep Learning for Natural Language Processing 10. Long Short-Term Memory Networks for Stock Forecasting 11. Generative Adversarial Networks for Faces 12. Section 3: Reinforcement Learning
13. Reinforcement Learning for Gaming 14. Deep Q-Learning for Maze Solving 15. Other Books You May Enjoy

Section 2: Deep Learning Applications

This section covers various deep learning applications in image processing, natural language processing, recommender systems, and predictive analytics. The reader will learn how to tackle recognition problems including image recognition and signal detection, programmatically summarize documents, conduct topic modeling, and forecast stock market prices.

This section comprises the following chapters:

  • Chapter 4, CNNs for Image Recognition
  • Chapter 5, Multilayer Perceptron for Signal Detection
  • Chapter 6, Neural Collaborative Filtering Using Embeddings
  • Chapter 7, Deep Learning for Natural Language Processing
  • Chapter 8, Long Short-Term Memory Networks for Stock Forecasting
  • Chapter 9, Generative Adversarial Networks for Faces
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