{"id":261,"date":"2023-02-08T23:28:43","date_gmt":"2023-02-08T22:28:43","guid":{"rendered":"http:\/\/gretsi.fr\/ressources-pedagogiques\/?p=261"},"modified":"2025-09-15T15:56:50","modified_gmt":"2025-09-15T13:56:50","slug":"strategie-bayesienne-en-science-des-donnees","status":"publish","type":"post","link":"https:\/\/gretsi.fr\/ressources-pedagogiques\/strategie-bayesienne-en-science-des-donnees\/","title":{"rendered":"Strat\u00e9gie bay\u00e9sienne en science des donn\u00e9es"},"content":{"rendered":"<p>Il s&rsquo;agit d&rsquo;un module d&rsquo;enseignement science des donn\u00e9es d&rsquo;une trentaine heures au total incluant cours, exercices et travaux pratiques. Il est centr\u00e9 sur la question du traitement de donn\u00e9es exp\u00e9rimentales. Il visite les concepts de mod\u00e8le de donn\u00e9es et de vraisemblances, information de Fisher et distance de Kullback, co\u00fbts et risques, estimation optimale, \u00e9chantillonnage stochastique et optimisation. Une part importante est consacr\u00e9e \u00e0 la question de la quantification d&rsquo;incertitudes. On introduit \u00e9galement des notions de comparaison de mod\u00e8les et des mod\u00e8les \u00e0 base de r\u00e9seaux de neurones. Une partie est \u00e9galement consacr\u00e9e aux propri\u00e9t\u00e9s asymptotiques. Il inclut plusieurs s\u00e9ances pratiques sur des cas concrets: ph\u00e9nom\u00e8ne thermique ou oscillatoire amorti, spectre de raies,&#8230;<\/p>\n<p><em>Le cours est largement au tableau et \u00e0 la craie&#8230;<\/em><\/p>\n<h3><\/h3>\n<p>&nbsp;<\/p>\n<h3><strong>Recueil d&rsquo;exercices<\/strong><\/h3>\n<ul>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesExo.pdf\">[PDF]<\/a> <span style=\"color: #000000\">Vraisemblance, Fisher, Fisher et Kulback, posterior, co\u00fbt et risque, estimation (exemple Gauss, exponentiel,&#8230;).<\/span><\/li>\n<\/ul>\n<h3><\/h3>\n<h3>Sujets de travaux pratiques<\/h3>\n<ul>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesDiversSimulTP.pdf\">[PDF]<\/a> <span style=\"color: #000000\">Travaux introductifs: simulation et observation (Gauss et uniforme, couple et corr\u00e9lation, m\u00e9lange de deux gaussiennes).<br \/>\n<\/span><\/li>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesEstimeGammaTP.pdf\">[PDF]<\/a> <span style=\"color: #000000\">Un exemple basique: estimation des param\u00e8tres d&rsquo;une densit\u00e9 Gamma&#8230;<\/span><\/li>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesThermiqueTP.pdf\">[PDF]<\/a> <span style=\"color: #000000\">Un exemple en thermique: estimation d&rsquo;un coefficient de diffusivit\u00e9 \/ convection<\/span><\/li>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesMixtureTP.pdf\">[PDF]<\/a> <span style=\"color: #000000\">Cas du m\u00e9lange de deux gaussiennes scalaire: identification des param\u00e8tres<\/span><\/li>\n<\/ul>\n<h3><\/h3>\n<h3>Un diaporama: \u00e9chantillonnage stochastique et MCMC<\/h3>\n<ul>\n<li><a href=\"http:\/\/giovannelli.free.fr\/Enseigne\/Bayes\/BayesSamplingDiapo.pdf\">[PDF]<\/a>\u00a0 <span style=\"color: #000000\">Variables continues et discr\u00e8tes, m\u00e9thode directes et MCMC, Gibbs et Metropolis-Hastings&#8230;<\/span><\/li>\n<\/ul>\n<p><!--more--><\/p>\n<table class=\"wp-block-table\">\n<tbody>\n<tr>\n<td>Auteur(s)<\/td>\n<td>Jean-Fran\u00e7ois Giovannelli<\/td>\n<\/tr>\n<tr>\n<td>Contact<\/td>\n<td>Giova@IMS-Bordeaux.fr<\/td>\n<\/tr>\n<tr>\n<td>Langue<\/td>\n<td>Fran\u00e7ais<\/td>\n<\/tr>\n<tr>\n<td>Licence<\/td>\n<td><i><a href=\"https:\/\/creativecommons.org\/choose\/\">Creative Commons<\/a><br \/>\n<\/i><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"<p>Il s&rsquo;agit d&rsquo;un module d&rsquo;enseignement science des donn\u00e9es d&rsquo;une trentaine heures au total incluant cours, exercices et travaux pratiques. Il est centr\u00e9 sur la question du traitement de donn\u00e9es exp\u00e9rimentales. Il visite les concepts de mod\u00e8le de donn\u00e9es et de vraisemblances, information de Fisher et distance de Kullback, co\u00fbts et risques, estimation optimale, \u00e9chantillonnage stochastique&hellip;&nbsp;<a href=\"https:\/\/gretsi.fr\/ressources-pedagogiques\/strategie-bayesienne-en-science-des-donnees\/\" class=\"\" rel=\"bookmark\">Lire la suite &raquo;<span class=\"screen-reader-text\">Strat\u00e9gie bay\u00e9sienne en science des donn\u00e9es<\/span><\/a><\/p>\n","protected":false},"author":15,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"off","neve_meta_content_width":70,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":""},"categories":[1],"tags":[],"niveau":[5,6],"theme2":[39,59],"type2":[50,51,53],"acf":[],"_links":{"self":[{"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/posts\/261"}],"collection":[{"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/users\/15"}],"replies":[{"embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/comments?post=261"}],"version-history":[{"count":16,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/posts\/261\/revisions"}],"predecessor-version":[{"id":353,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/posts\/261\/revisions\/353"}],"wp:attachment":[{"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/media?parent=261"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/categories?post=261"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/tags?post=261"},{"taxonomy":"niveau","embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/niveau?post=261"},{"taxonomy":"theme2","embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/theme2?post=261"},{"taxonomy":"type2","embeddable":true,"href":"https:\/\/gretsi.fr\/ressources-pedagogiques\/wp-json\/wp\/v2\/type2?post=261"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}