Week08

Tips and tricks in supervised learning

Interactive session, Monday March 17

Slides

Screencast

Weekly lecture:

Slides: tips and tricks in supervised learning

Lecture videos:

1. Overview
2. Scikit-learn examples
   • notebook
3. Over-fitting and regularization
4. Regularization in scikit-learn
   • notebook
5. Bias-variance tradeoff
6. Cross-validation
   • notebook
7. Ensemble learning and Random forests

Syllabus:

Hal Daum¨¦ III, A course in Machine Learning

• Ch. 5 Practical issues, sec. 5.0-5.6 (p.55-66), except precision-recall curves, ROC curves and AUC curves.

Jurafsky and Martin, Speech and language processing, 3rd ed. draft, Jan 12, 2025

• Chapter 4, section 4.7 "Evaluation: Precision, Recall, F-measure", section 4.8 "Test sets and Cross-validation"
• Chapter 5, section 5.7 "Regularization"

Marsland

• Chapter 2, section 2.5 (Not the formulas)
• Chapter 13: Introduction, 13.2 Bagging, 13.3 Random forest

Weekly exercises

There are no new weekly exercises for this week. The program for the group sessions is to work on mandatory 2 and the notebooks linked above.