Introduction
Learn what deep learning is and how it relates to machine learning and artificial intelligence.
๐ Programming Tutorial
Deep Learning
Deep structured learning or hierarchical learning, or deep learning in short, is part of the family of machine learning methods, which are themselves a subset of the broader field of Artificial Intelligence.
DL Tutorial Index
13 Topics๐ง Deep Learning
Brief History
Learn how deep learning developed over time.
Deep Feedforward Networks
Learn feedforward networks, also called multilayer perceptrons.
Gradient-Based Learning
Learn how networks are trained using gradient descent and cost functions.
Output Units
Learn the choice of output units for different kinds of tasks.
Hidden Units
Learn the types of hidden units and activation functions.
Architecture Design
Learn how depth and width are chosen when designing a network.
Dataset Augmentation
Learn how extra training data is created by transforming existing data.
Noise Robustness
Learn how adding noise makes models more robust.
Semi-Supervised Learning
Learn how labeled and unlabeled data are used together.
Multi-Task Learning
Learn how sharing examples from several tasks improves generalization.
Early stopping
Learn how training is stopped when validation error stops improving.
Parameter Tying and Sharing
Learn how parameters are tied or shared to reduce the model size.
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