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Detailed Course Information

 

Fall 2012
Jan 22, 2022
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Information Select the desired Level or Schedule Type to find available classes for the course.

CS 57800 - Statistical Machine Learning
Credit Hours: 3.00. This introductory course will cover many concepts, models, and algorithms in machine learning. Topics include classical supervised learning (e.g., regression and classification), unsupervised learning (e.g., principle component analysis and K-means), and recent development in the machine learning field such as variational Bayes, expectation propagation, and Gaussian processes. While this course will give students the basic ideas and intuition behind modern machine learning methods, the underlying theme in the course is probabilistic inference. Typically offered Fall.
3.000 Credit hours

Syllabus Available
Levels: Graduate, Professional, Undergraduate
Schedule Types: Lecture

Offered By: College of Science
Department: Computer Science

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette

Learning Outcomes: 1. Have students prepared to either conduct PhD research in the machine learning area or apply it to other application domain, such as computational biology, materials science and social science.


Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

Prerequisites:
GR-CS 57800 Requisites

General Requirements:

Student Attribute: GR
May not be taken concurrently.  )
or
Course or Test: MA 16200
Minimum Grade of D-
May not be taken concurrently.  )
or
Course or Test: MA 35100
Minimum Grade of D-
May not be taken concurrently.  )
or
Course or Test: STAT 41600
Minimum Grade of D-
May not be taken concurrently. )


Short Title: Statistical Machine Learning

Course Configurations:

Configuration 1: 3.0 Credits
Schedule Type Weekly Contact Hours Instructional Credit Distribution
Lecture 3 3.0

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