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Pierre-Edouard Portier ad7d179f87 init .gitignore
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ca_experiment
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data
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_bookdown.yml
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01_intro.R
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01_intro.Rmd
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02_a_application_abalone.Rmd
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02_b_breviaire_proba_stat.Rmd
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02_moindres_carres_slides.Rmd
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02_moindres_carres.R
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02_moindres_carres.Rmd
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03_tikhonov_slides.Rmd
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03_tikhonov.R
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03_tikhonov.Rmd
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04_validation_croisee_slides.Rmd
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04_validation_croisee.R
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04_validation_croisee.Rmd
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05_b_svd_pca_slides.Rmd
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05_b_svd_pca.Rmd
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05_presentation_svd_slides.Rmd
petites modifications
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05_presentation_svd.R
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05_presentation_svd.Rmd
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05_svd_pca.R
functions to perform a factorial analysis based on pca
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06_matrice_definie_non_negative.Rmd
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07_multiplicateurs_de_lagrange.Rmd
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08_derivation_svd.Rmd
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09_puissance_iteree_valeur_propre.Rmd
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10_puissance_iteree_svd.Rmd
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11_projecteurs_slides.Rmd
some slides done
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11_projecteurs.Rmd
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12_factorisation_qr.R
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12_factorisation_qr.Rmd
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13_puissance_iteree_par_blocs.Rmd
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14_geometrie_ridge_svd_slides.Rmd
some slides done
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14_geometrie_ridge_svd.R
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14_geometrie_ridge_svd.Rmd
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15_loocv_slides.Rmd
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15_loocv.R
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15_loocv.Rmd
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16_biais_variance_estimateur_slides.Rmd
ajout de diapositives sur le biais et la variance d'un estimateur
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16_biais_variance_estimateur.Rmd
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17_biais_variance_ridge.Rmd
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18_kernel_ridge_regression_slides.Rmd
ajout de diapositives pour présenter la régression ridge à noyau
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18_kernel_ridge_regression.R
implémentation de la régression ridge à noyau gaussien
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18_kernel_ridge_regression.Rmd
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19_nystroem_approximation_slides.Rmd
ajout de diapositives pour expliquer l'approximation de Nystroem
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19_nystroem_approximation.Rmd
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20_tp_dilemme_biais_variance_sujet.Rmd
ajout d'un TP pour expérimenter sur le dilemme biais variance sur un jeu de données synthétique
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20_tp_dilemme_biais_variance.Rmd
ajout d'un TP pour expérimenter sur le dilemme biais variance sur un jeu de données synthétique
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21_b_tp_projection_aleatoire_housing_pca.Rmd
ajout d'un TP pour expérimenter sur la projection aléatoire et l'analyse factorielle apr PCA sur le jeu de données California Housing
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21_c_tp_projection_aleatoire_housing_elm.Rmd
ajout d'un TP pour expérimenter sur la projection aléatoire et l'analyse factorielle apr PCA sur le jeu de données California Housing
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21_tp_projection_aleatoire_sujet.Rmd
ajout d'un TP pour expérimenter sur la projection aléatoire et l'analyse factorielle apr PCA sur le jeu de données California Housing
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21_tp_projection_aleatoire.Rmd
ajout d'un TP pour expérimenter sur la projection aléatoire et l'analyse factorielle apr PCA sur le jeu de données California Housing
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22_tp_kernel_ridge_regression_sujet.Rmd
ajout d'un TP sur la régression ridge à noyau
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22_tp_kernel_ridge_regression.Rmd
ajout d'un TP sur la régression ridge à noyau
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23_exercices.R
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99_references.Rmd
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index.Rmd
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intro_to_ml.bib
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intro_to_ml.Rproj
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LICENSE
Initial commit
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make_all_chapters
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make_book
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make_book_old
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make_chapter
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make_slides
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make_slides_archive
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make_src_archive
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make.R
to work with beamer, call to render w/o pdf_document()
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Makefile
To compile Rmd files to PDF with a Makefile
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pad.R
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preamble.tex
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README.md
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README.md

intro_to_ml

Introduction to Machine Learning.

Description
Introduction to Machine Learning.
Readme 1.9 MiB
Languages
R 91.6%
Shell 6.1%
TeX 2.2%