Book Content
chapters • 5h56m total length
1. Introduction to Markov Process
2. Hidden Markov Models
3. State Inference: Predicting the states
4. Parameter Inference using Maximum Likelihood
5. Parameter Inference using Bayesian Approach
6. Time Series: Predicting Stock Prices
7. Natural Language Processing: Teaching machines to talk
8. 2D-HMM for Image Processing
9. Reinforcement Learning: Teaching a robot to cross a maze
