SD204 - linear models (2016-2018)

Linear models and a bit of sparsity
linear models
sparse models

This is an undergraduate course on linear models.

Slides and Courses

  1. Introduction: LeastSquare_1D_en.pdf, LeastSquare_1D_en.ipynb, LeastSquare_1D_en.html

  2. Least squares : LeastSquare_Def_en.pdf, LeastSquare_1D_fr.ipynb, LeastSquare_Def_en.html

  3. Least squares (properties) : LeastSquare_Prop_fr.pdf

  4. SVD: SVD_en.pdf (in French), SVD.ipynb, SVD.html

  5. PCA: PCA_en.pdf (in French), PCA.ipynb, PCA.html

  6. IntroIC: IntroIC_en.pdf (in French), IntroIC.ipynb, IntroIC.html

  7. Bootstrap: Bootstrap_en.pdf,

  8. IntroTests: IntroTests_en.pdf, forward_variable_selection.ipynb, forward_variable_selection.html

  9. Ridge: Ridge_en.pdf, Ridge_en.ipynb, Ridge_en.html

  10. Lasso: Lasso_en.pdf, Lasso_fr.ipynb, Lasso_fr.html, functions_Lasso.py, prox_collection.py

  11. Coordinate descent: CD_en.pdf (in French), CD_fr.ipynb, CD_fr.html

  12. GLM: GLM_en.pdf (in French), GLM_fr.ipynb, GLM_fr.html

  13. Generalization: Generalization_en.pdf, Generalization_fr.ipynb, Generalization_fr.html

  14. Categorical variables: CategoricalVariables.ipynb, CategoricalVariables.html