Introduction : Statistical Machine Learning 소개 001, 002

Part 1: 

• Statistical Machine Learning 

  • Purpose of Statistical Mahcine Learning [Lecture]

  • Types of Statistical Machine Learning: Parametric vs Non-Parametric  [Lecture]

  • Prediction vs Interpretation []

  • Model Assessment for Regression and Classfication 003, 004

  • Non-parametric Appraoch Example:  K-NN 

  • Bias-Variance Trade-Off

• Other Model Evaluation Methods for Regression: AIC, BIC, Cp, adj R2, 

• Other Model Evaluation Methods for Classification: ROC, AUC

• Resampling Method: Cross Validation for Model Assessment

• Resampling Method: Boostrap for Quantifying Uncertainty

Part 2: Regression Problem

• Chapter 3: 001, 002, 003

• Chapter 6: 001, 002, 003, 004

• Chapter 7: 001, 002

Part 3: Classification Problem

• Chapter 4: 001

• Chapter 8: 001

• Chapter 9: 001

• Chapter 10: 001

Part 4: Unsupervised Learning

• Chapter 12: 001

• Graphical Models

Project 1: Regression Problem 001, 002, 003, 004, 005

Project 2: Classification Problem 001, 002, 003, 004, 005