Deep Learning. Notes on deep learning

Introduction

• Credits
• AI overview
• Deep learning overview
• AI history

Foundational ideas

• Essential statistics
• Measuring performance
• Bayes' rule
• Curves and surfaces
• Information theory

Machine learning basics

• Classification
• Training and testing
• Overfitting and underfitting
• Data preparation
• Classifiers
• Ensembles

Deep learning basics

• Neural networks
• Backpropagation
• Optimizers

Deep learning

• Convolutional neural networks
• Convnets in practice
• Autoencoders
• Recurrent neural networks
• Attention and transformers
• Reinforcement learning
• Generative adversarial networks
• Large language models

From models to systems

• Coding agents