CSE-6363-003 Machine Learning, Fall 2016

Syllabus

• Syllabus

TA

• Hongchang Gao
• Office: ERB-407
• Office hours: Monday 14:00 - 17:00 hrs

  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. Introduction to Big Data
  13. Introduction to Data Science
  14. Exploratory Data Analysis

  References to other Algorithms

  • References

  Exams

  • Midterm 1, October 13, 2016
  • Midterm 2, December 6, 2016

  Prepare for the Exams

  1. Midterm 1, , 2016: Study topics 1 - 7
     • Introduction to Machine Learning
     • Decision Trees
     • Rule-based Learning
     • Association Rules
     • Clustering
     • Instance-based Learning
     • Hypothesis Testing
  2. Midterm 2, , 2016: Study topics ? - ?