Jesus A. Gonzalez Web Page


CSE-6363-002 Machine Learning, Spring 2019

Syllabus

Teaching Assistant

Lectures

  1. Introduction to Machine Learning
  2. Decision Trees
  3. Rule-based Learning
  4. Association Rules
  5. Clustering
  6. Instance-based Learning
  7. Hypothesis Testing
  8. Bayesian Learning - Naive Bayes
  9. Bayesian Learning - Bayesian Networks
  10. Neural Networks
  11. Support Vector Machines
  12. Boosting
  13. Introduction to Big Data
  14. Introduction to Data Science
  15. Exploratory Data Analysis
  16. PAC Learning
  17. Gradient Boosting Machine

References to other Algorithms

Project (50%) (Teams of 2 Students)

Exams (30%)

Assignments (20%)

Prepare for the Exams

  1. Midterm 1, Feb 16, 2019: Study topics ? - ?
  2. Midterm 2, May 4, 2019: Study topics ? - ?