COMP-SCI 5565 Introduction to Statistical Learning
Contact: tzheng@umkc.edu
Location: Bloch Heritage Hall Room 6
Time: Tuesdays and Thursdays 10:00-11:15 AM
Office Hours: Mondays 10:00-11:00 AM （Flarsheim Hall 410A)
Textbooks:
An Introduction to Statistical Learning
Machine Learning with Python Tutorial
Lectures and Labs:
The slides and code only can be used for the purpose of review or preparation for exams by the students enrolling in this course. Please do not distribute them to other places, which is illegal.
| Time | Lecture/Lab | Materials |
|---|---|---|
| Week 1 Tuesday | Course Introduction | |
| Week 1 Thursday | Introduction to Python | ipynb Auto.csv |
| Week 2 Tuesday | Statistical Learning | |
| Week 2 Thursday | Linear Regression | |
| Week 3 Tuesday | Linear Regression | |
| Week 3 Thursday | Linear Regression | ipynb Advertising.csv Credit.csv |
| Week 4 Tuesday | Classification | |
| Week 4 Thursday | Classification | ipynb Default.xlsx Smarket.csv |
| Week 5 Tuesday | Resampling and Evaluation | |
| Week 5 Thursday | Resampling and Evaluation | ipynb |
| Week 6 Tuesday | Model Selection and Regularization | |
| Week 6 Thursday | Model Selection and Regularization | ipynb Hitters.csv Hitters_X_train.csv Hitters_X_test.csv Hitters_y_train.csv Hitters_y_test.csv |
| Week 7 Tuesday | Moving Beyond Linearity | |
| Week 7 Thursday | Moving Beyond Linearity | ipynb Wage.csv |
| Week 8 Tuesday | Tree-based Methods | |
| Week 8 Thursday | Tree-based Methods | ipynb Boston.csv Heart.csv |
| Week 10 Tuesday | Support Vector | |
| Week 10 Thursday | Support Vector | ipynb Khan_xtest.csvKhan_xtrain.csvKhan_ytest.csvKhan_ytrain.csv |
| Week 11 Tuesday | Deep Learning | |
| Week 11 Thursday | Unsupervised Learning | |
| Week 12 Tuesday | Unsupervised Learning | ipynb USArrests.csv |
| Week 12 Thursday | Hypothesis Testing | |
| Week 13 Tuesday | Hypothesis Testing | ipynb |
| Week 13 Thursday | Survial Analysis | |
| Week 15 Tuesday | Review | |
| Week 16 Thursday | Review |