Introduction to Machine Learning

Introduction to Machine Learning

Introduction to Machine Learning

Instructor: David Banks

July 14, 2023

About the Short Course: 1 Day Course

‚ÄčThis course describes nonparametric regression, including the additive model and its generalizations, also the LASSO, and LARS. Then it proceeds to classification (SVMs, random forests, boosting). The Curse of Dimensionality is described in both contexts. Bagging and stacking are covered. There is some coverage of cluster analysis, and some text analytics. The emphasis is upon the strengths and weaknesses of the tools, and guidance on when a particular method should be used.

In-Person Event. Location Of Short Courses: University of Ottawa


Who is this course for?

People with some statistical background, but not experts in this area.

Level Of Instruction: Intermediate


Learning Outcomes

  1. Data science overview
  2. Key ideas in nonparametric regression
  3. Methods for model assessment and quantified prediction
  4. Non -parametric regression methods
  5. Recent advances in variable selection methodology
  6. Classification techniques: SVMs and Random Forests
  7. The power of ensembles

Course Material

Lectures delivered from pdf slides that are shared with attendees.

Delivery Structure

Rather dull lecture format, I'm afraid. But I do try to interact with the audience.

Knowledge Assumed

Multiple linear regression, basic probability.


About the instructor: David Banks

David Banks obtained an M.S. in Applied Mathematics from Virginia Tech in 1982, followed by a Ph.D. in Statistics in 1984. He won an NSF Postdoctoral Research Fellowship in the Mathematical Sciences, which he took at Berkeley, working with David Blackwell. In 1986 he was a visiting assistant lecturer at the University of Cambridge, and then joined the Department of Statistics at Carnegie Mellon in 1987. In 1997 he went to the National Institute of Standards and Technology, then served as chief statistician of the U.S. Department of Transportation, and finally joined the U.S. Food and Drug Administration in 2002. In 2003, he returned to academics at Duke University.

Affiliations: Dept. of Statistical Science, Duke University