stable
How to Tutorials
How to: Machine Learning
Supervised Learning
Linear Regression
Logistic Regression
k-Nearest Neighbours
Random Forest
Bayesian Linear Regression
Gaussian Process Regression
Unsupervised Learning
k-means
How to: Reinforcement Learning
Introduction
Problem Setup
Value Function
Action-Value Function
Value Iteration
What is Value iteration?
Markov Decision Processes
Example Environment - Gridworld
Computing the Value Function and Policy
Summary
Advanced Applications
Advanced: Machine Learning
Advanced: Reinforcement Learning
Theories
Regression
Classification
Appendix
A: Linear Algebra
B: Vector and Matrix Identities
C: Vector and Matrix Calculus
Central AI
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Index
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Index