Foundations of Statistical Learning
- probability and random variables
- Expectation, Inequalities
- Convergence of random variables
- Models, statistical inference and learning
- Estimating the CDF and Statistical Functionals
- Bootstrap
- Parametric Inference
- Hypothesis Testing
- Bayesian Inference
- Inference about Independence
- Variational Inference
- Linear Regression
- Undirected probabilistic graphical models
- Classification
- Markov Process
- Simulation Methods
- Stochastic Processes