Book Content
chapters • 9h28m total length
1. Bayesian Network Fundamentals
2. Markov Network Fundamentals
3. Inference: Asking Questions to Models
4. Approximate Inference Methods: Sampling
5. Model Learning: Parameter Estimation in Bayesian Networks
6. Model Learning: Parameter Estimation in Markov Networks
7. Specialized Models
