- Decision trees
- First-order inductive learning
- Incremental learning: Version spaces
- Uncertainty
- Bayesian networks

- Learning parameters of Bayesian networks
BME, MAP, ML, EM algorithm- Learning structures of Bayesian networks
- Gaussian Mixture Models

- kNN classifier, neural network classifier, support vector machine (SVM) classifier

- Clustering
Distance measures, k-means clustering, nearest neighbor clustering- Kernel Density Estimation
- Ensemble Learning
- Reinforcement Learning
- Computational Learning Theory

- Artificial Intelligence: A Modern Approach (Third Edition), Stuart Russel, Peter Norvig, Prentice Hall, 2010, Chapters 13, 14, 18-21
- Machine Learning: A Probabilistic Perspective, Kevin Murphy, MIT Press 2012