ECE 6254 - Statistical Machine Learning

Spring 2018

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Exam information is on the Schedule page.

This course will provide an introduction to the theory of statistical learning and practical machine learning algorithms with applications in signal processing and data analysis. In contrast to most traditional approaches to statistical inference and signal processing, in this course we will focus on how to learn effective models from data and how to apply these models to practical signal processing problems. We will approach these problems from the perspective of statistical inference. We will study both practical algorithms for statistical inference and theoretical aspects of how to reason about and work with probabilistic models. We will consider a variety of applications, including classification, prediction, regression, clustering, modeling, and data exploration/visualization.

Important Links and Information

 

Office Hours

  • Dr. Anderson: M F  9:00-10:30 in TSRB 543
  • You Wang: T  2:00-5:00 TSRB 5th floor landing near stairs
  • Andrew McRae:  F 10:00-1:00 TSRB 5th floor landing near stairs

Professor: David V. Anderson