HMMA308 - Apprentissage statistique (2018-2019)

This course is in French, and deals with Machine Learning, mostly supervised learning.

Level set for Lasso Level set for Adaptive Lasso (sqrt) Level set for Adaptive Lasso (log)

Syllabus:

version 2018-2019

Cours:

  1. Intro Machine Learning: IntroML_slides.pdf

  2. Régression logistique/LDA: RegressionLogistique_slides.pdf

  3. Validation Croisée: CrossValidation_slides.pdf

  4. SVD: SVD_slides.pdf; SVD.ipynb

  5. Ridge: Ridge_slides.pdf, Ridge_fr.ipynb

  6. Lasso: Lasso_slides.pdf, Lasso_fr.ipynb, functions_Lasso.py, prox_collection.py

  7. Méthodes non-linéaires, GAM et splines: Splines_GAM_slides.pdf, GAM.ipynb

  8. Arbres : arbres_slides.pdf

  9. Bagging et forêts aléatoires : ForetsAleatoires_slides.pdf

  10. SVM : svm_slides.pdf

  11. Clustering : clustering_slides.pdf

TPs:

  1. knn_tp.pdf , knn_tp_corr.pdf, tp_knn_source.py, tp_knn_script.py, tp_knn_script_corr.py

  2. perceptron_tp.pdf, tp_perceptron_source.py, tp_perceptron_script.py, TP_perceptron.ipynb

  3. arbres_tp.pdf

  4. svm_tp.pdf, svm_tp_sources.zip

  5. clustering_tp.pdf, kmeans.py, gap.py, china.jpg

Projet final:

project_2018-2019.pdf