Instructor: Kavitha Chandra
Computational Data-Driven Modeling (CDM) II is the second in a sequence of two courses designed to introduce the student to skills in exploratory data analysis and data-driven computational modeling. CDM-II extends the students’ knowledge on application of regression and classification algorithms in CDM-1 to more complex structures such as Bayesian networks and Hidden-Markov models. The focus will be on time-varying data using time-series and state-space models such as Kalman filters, Markov Processes and Particle filters for prediction and forecasting. The application of neural networks and deep-learning will be discussed. The course applies a Bayesian modeling perspective to machine learning algorithms.