STA 325: Data Mining and Machine Learning
This is a rough schedule for the course and will be updated regularly. Please check this frequently for adjustments. Announcements will be posted here and made in class. It will be up to you to keep up to date on all class announcements and web announcements made for the course. Read along in Hoff before coming to class.
The course syllabus can be found here Syllabus: things you need to know about the course!
All announcements will be posted on Sakai.
Please check for updates to the course notes regularly as they are being written and updated quite
frequently. (I tend to update them before or after each class on Tuesday's and Thursdays).
Find a quick review of R that I expect you should have no trouble completing.
Module 0: An introduction to data mining and machine learning
Module 1: An introduction to data mining and machine learning, Part II
Module IR: Information Retrieval
Module IR: Locality Sensitive Hashing
Module 2: Introduction to Statistical Machine Learning
Module US: Unsupervised Learning (Ch 10 ISLR)
Module 3: Linear Regression
Module 4: Classification: Logistic Regression and Linear Discrimminant Analysis
Module 5: Resampling Techniques
Module 8: Decision Trees