TA

• 徐崴雋

• HackMD

Course slides:

• • 02/26: Course introduction (slides)

  • 03/05: Machine Learning for Beginner (slides) (code)

  • 03/12: Linear Regression and Ridge Regression (slides) (code)

  • 03/19: Logistic Regression and Imbalanced Problem (slides) (code1) (code2)

  • 03/26: Clusrering: Kmeans and Hierarchical Clustering (slides) (code1) (code2)

  • 04/09: Principal Component Analysis (slides) (code1) (code2)

  • 04/16: Linear Discriminant Analysis

  • 04/23: Feature Selection (slides) (code1)(code2)(code3)

  • 04/30: Ensemble Methods: Bagging (slides) (code)

  • 05/07: Ensemble Methods: Boosting

  • 05/14: Gradient Boosting Machine (slides)

  • 05/21: Final Project Status Check

  • 05/28: From Linear to Nonlinear: Kernel Trick (slides)(slides)

  • 06/04: Invited Speaker

  • 06/11: Final Project Presentation

Bi-weekly Exercise

• • 20210312_problem_set (code)

  • 20210326_problem_set (code)

  • 20210416_problem_set (data) (code)

  • 20210507_problem_set (code)

  • 20210528_problem_set