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Deep Learning
Fundamentals & Summary
Deep Learning Landscape
Introduction to Deep Learning
Feedforward Neural Networks
Probability & Statistics in DL
Loss Functions
Convolutional Neural Networks
Recurrent Neural Networks
Generative Models
Graph Neural Networks
Large Language Models
Foundation Models
New Sequence Model Paradigms
Optimization & Regularization
DL Frontiers
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Table of Contents
A New Brief History of Deep Learning
The Afterglow of a Golden Age
Scholars in Exile
The Age of Exploration
The Imperial Age
The One and Only Great Treasure
The Three Waves of Deep Learning
Before Deep Learning
The First Wave: Cybernetics
The Second Wave: Connectionism
The Third Wave: Deep Networks
Deep Neural Networks
Neural Network Architecture
Universal Approximation Theorem
Vanishing Gradients
Exploding Gradients
Common DNN Architectures
MLP
CNN
RNN
Generative Models
Transformer
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