Course 3 : Decision Trees and Ensemble methods
Lecture 3: Lecture 3a.pdf, Lecture3b.pdf and Lecture3c.pdf.
Notebooks of Lecture 3a : Lecture3a.ipynb, Lecture3b.ipynb.
Datasets : PimaDiabets.csv
Lab 3 : Lab3.pdf. Datasets : rent.csv, hostel_factors.csv
Additional websites on Decision Trees : visualization and basics on decision trees
Additional website on Random Forest : Importance Measures with RF
More on tabular data
Foundation models for tabular data
McElfresh, Duncan, et al. When do neural nets outperform boosted trees on tabular data?. Advances in Neural Information Processing Systems 36 (2024). pdf
Kim, Myung Jun, Léo Grinsztajn, and Gaël Varoquaux. CARTE: pretraining and transfer for tabular learning. arXiv preprint arXiv:2402.16785 (2024). pdf
Course 2 : Beyond OLS
Lecture 2 : Lecture2.pdf
Notebook of Lecture 2 : Lecture2.ipynb
Practical Session 2 : PracticalSession2.pdf
Datasets : diabetes.csv, Hitters.csv
Course 1 : Basics on supervised learning and optimisation
Lecture 1a : Lecture1a.pdf
Lecture 1b : Lecture1b.pdf
Lecture 1c : Lecture1c.pdf
Practical Session 1 : PracticalSession1.pdf