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Contents:
Part I: Applied Math and Machine Learning Basics
Part II: Modern Practical Deep Networks
Part III: Deep Learning Research
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Welcome to dl’s documentation!
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Welcome to dl’s documentation!
¶
Contents:
Part I: Applied Math and Machine Learning Basics
5 Machine Learning Basics
Part II: Modern Practical Deep Networks
8 Optimization for Training Deep Models
9 The convolutional Networks
11 Practical Methodoloogy
12 Applications
Part III: Deep Learning Research
14 Autoencoders
15 Representation Learning
16 Structured Probablistic Models for Deep Learning
17 Monte Carlo Methods
18 Confronting the Partition Function
19 Approximate Inference
20 Deep Generative Models
Extra
Reinforcement Learning
Indices and tables
¶
Index
Module Index
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