Machine Learning Topics Covered

• Supervised Learning: Decision trees, nearest neighbors, linear classifiers and kernels, neural networks, linear regression; learning theory; bagging and boosting; feature selection.
• Unsupervised Learning: Clustering, graphical models, EM, PCA, factor analysis, manifold learning.
• Reinforcement Learning: Value iteration; policy iteration; TD learning; Q learning; actor-critic.
• Other Topics: Bayesian learning, online learning.