Data Analysis (Fall 2015)
Course Slides:
09/17: course introduction (slides)
09/24: basic concept and naive bayes (slides)
10/01: basic model evaluation (including parameter tuning) and k-nearest neighbors (slides)
10/08: A tutorial to Matlab (slides)
10/15: A tutorial to Matlab (Data) (Code)
10/22: Decision Tree (slides)
10/29: Decision Tree and linear regression(slides)
11/05: Ridge Regression and LASSO
11/12: Midterm Exam
11/19: Clustering (slides)
11/26: Clustering
12/03: Dimension Reduction (PCA) (slides)
12/10: Dimension Reduction (LDA)
12/17: Support Vector Machine (slides)
12/24: Support Vector Machine
12/31: Questions for final project
01/07: Final project presentation
01/14: Final project presentation
Project:
Demo code (download)
Face Recognition Data set (download)
Hand Digit Recognition Data set (download)
Text Mining Data set (download)
Regression Data set (download)
Exams:
Mid-term exam
previous mid-term exam(download)
Final project