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Deep Learning Architectures

Overview of attention for book
Cover of 'Deep Learning Architectures'

Table of Contents

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    Book Overview
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    Chapter 1 Introductory Problems
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    Chapter 2 Activation Functions
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    Chapter 3 Cost Functions
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    Chapter 4 Finding Minima Algorithms
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    Chapter 5 Abstract Neurons
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    Chapter 6 Neural Networks
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    Chapter 7 Approximation Theorems
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    Chapter 8 Learning with One-dimensional Inputs
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    Chapter 9 Universal Approximators
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    Chapter 10 Exact Learning
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    Chapter 11 Information Representation
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    Chapter 12 Information Capacity Assessment
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    Chapter 13 Output Manifolds
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    Chapter 14 Neuromanifolds
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    Chapter 15 Pooling
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    Chapter 16 Convolutional Networks
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    Chapter 17 Recurrent Neural Networks
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    Chapter 18 Classification
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    Chapter 19 Generative Models
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    Chapter 20 Stochastic Networks
Attention for Chapter 9: Universal Approximators
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