Components of learning , learning models , geometric models , probabilistic models , logic models , grouping and grading , learning versus design , types of learning , supervised , unsupervised , reinforcement , theory of learning , feasibility of learning , error and noise , training versus testing , theory of generalization , generalization bound , approximation generalization trade off , bias and variance , learning curve

Linear classification , Univariate linear regression , Multivariate linear regression , Regularized regression , Logistic regression , Perceptrons , Multilayer neural networks , learning neural networks structures , support vector machines , soft margin SVM , going beyond linearity , generalization and overfitting , regularization , validation.

Nearest neighbour models , K,means , clustering around medoids , silhouttes , hierarchical clustering , k,d trees , locality sensitive hashing , non,parametric regression , ensemble learning , bagging and random forests , boosting , meta learning.

Decision trees , learning decision trees , ranking and probability estimation trees , regression trees , clustering trees , learning ordered rule lists , learning unordered rule lists , descriptive rule learning , association rule mining , first,order rule learning

Passive reinforcement learning , direct utility estimation , adaptive dynamic programming , temporal, difference learning , active reinforcement learning , exploration , learning an action utility function , Generalizationinreinforcementlearning,policysearch,applicationsingameplaying,applicationsin robot control.