Concepts of machine learning; probability and statistics in machine Learning; decision trees; artificial neural networks; Bayesian decision theory: Bayesian network, Naive Bayes classifier,and EM algorithm; instance-based learning: nearest neighbor learning and adial basis functions; clustering: k-mean clustering, support vector machine, and hidden Markov models; feature selection and dimensionality reduction; combining multiple learners and assessment of classification algorithms; applying machine learning techniques to other domains: health care, biomedicine, and disaster management