Introduction to Machine Learning

Over the past few decades, the field of Machine Learning has matured significantly, drawing ideas from several disciplines including Statistics, Optimization, and Artificial Intelligence. Applications of Machine Learning have led to important advances in a wide variety of domains ranging from Internet applications to scientific problems. This talk will give a gentle tutorial introduction to Machine Learning with broad overview on four families of models and methods: predictive models, graphical models, online learning, and exploratory data analysis. The talk will discuss the main idea behind some of key approaches in each family and the problems where they are applicable. A wide variety of applications including text analysis, recommendation systems, climate sciences, and finance will be discussed.