AI Learning Models

The emphasis is on understanding the ideas, experimenting with them, and seeing how they can be applied in practice.

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1. Data Representation

▶ Data and Features in AI

▶ Feature Engineering in AI

▶ Representation Learning in AI

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2. Classical ML Models

▶ Support Vector Machine (SVM)

▶ Naive Bays

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3. Neural Network Models

▶ Neural Network Fundamentals - Part 1: Understanding How Neural Networks Work

▶ Neural Network Fundamentals - Part 2: Training Neural Networks

▶ Activation Function and Non-Linearity in Neural Networks

▶ Normalization of Inputs in Neural Networks

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4. Attention & Transformers

(WIP)

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5. Generative/Foundation Models

(WIP)

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Relevant Link(s)

AI in Context Main Page