CSE-6363-002 Machine Learning, Fall 2016

Syllabus

• Syllabus

TA

• Armin Parchami
• Email: mostafa.parchami@gmail.com
• Office: ERB-403
• Office hours: Mon-Wed 2:00pm to 3:30pm

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 17, 2016
• Midterm 2, December 7, 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 ? - ?