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Introduction to Deep Learning Using R

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Cover of 'Introduction to Deep Learning Using R'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Deep Learning
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    Chapter 2 Mathematical Review
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    Chapter 3 A Review of Optimization and Machine Learning
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    Chapter 4 Single and Multilayer Perceptron Models
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    Chapter 5 Convolutional Neural Networks (CNNs)
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    Chapter 6 Recurrent Neural Networks (RNNs)
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    Chapter 7 Autoencoders, Restricted Boltzmann Machines, and Deep Belief Networks
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    Chapter 8 Experimental Design and Heuristics
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    Chapter 9 Hardware and Software Suggestions
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    Chapter 10 Machine Learning Example Problems
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    Chapter 11 Deep Learning and Other Example Problems
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    Chapter 12 Closing Statements
Attention for Chapter 7: Autoencoders, Restricted Boltzmann Machines, and Deep Belief Networks
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