[{"command":"insert","method":null,"selector":".course-modal-ajax-placeholder-968260","data":"\u003Cdiv class=\u0022container content-rte\u0022\u003E\n \u003Cdiv class=\u0022row\u0022\u003E\n \u003Cdiv class=\u0022box col-md-6 bg-primary text-white\u0022\u003E\n \u003Ch2 class=\u0022h1 text-left\u0022\u003E Mod\u00e8les lin\u00e9aires g\u00e9n\u00e9ralis\u00e9s et extensions\n\u003C\/h2\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EECTS :\n 4\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ESemestre calendaire :\n Semester 1\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ED\u00e9tail du volume horaire\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan class=\u0022field__label h4 mt-5 \u0022\u003ECours magistraux :\u003C\/span\u003E\n \u003Cspan\u003E10.5\u003C\/span\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan class=\u0022field__label h4 mt-5 \u0022\u003ETravaux pratiques :\u003C\/span\u003E\n \u003Cspan\u003E31.5\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ELangue d\u0026#039;enseignement\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003EAnglais\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EEnseignement \u00e0 distance\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003Enon\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022box col-md-6\u0022\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EPr\u00e9requis\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003E\u003Cp\u003EProbability and statistics at B.Sc. level\nProbabilit\u00e9s et statistiques niveau L3\u003C\/p\u003E\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EProgramme \/ plan \/ contenus\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003E\u003Cp\u003EEn Fran\u00e7ais :\u003C\/p\u003E\n\u003Cul\u003E\n\u003Cli\u003EMoindres carr\u00e9s ordinaires, Mod\u00e8les lin\u00e9aires, mod\u00e8les lin\u00e9aires g\u00e9n\u00e9ralis\u00e9s.\u003C\/li\u003E\n\u003Cli\u003ES\u00e9lection de variables.\u003C\/li\u003E\n\u003Cli\u003EMod\u00e8les lin\u00e9aires avec contraintes de p\u00e9nalisation l1 ou l2 sur les coefficients (Lasso, Ridge).\u003C\/li\u003E\n\u003C\/ul\u003E\n\u003Cp\u003EIn English:\u003C\/p\u003E\n\u003Cul\u003E\n\u003Cli\u003EOrdinary least squares, linear models, generalized linear models.\u003C\/li\u003E\n\u003Cli\u003EVariable Selection.\u003C\/li\u003E\n\u003Cli\u003ELinear models with constraints l1 or l2 penalty on coefficients (Lasso, Ridge).\u003C\/li\u003E\n\u003C\/ul\u003E\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EObjectifs d\u0026#039;apprentissage\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003E\u003Cp\u003EEn Fran\u00e7ais :\nL\u0027exploitation des donn\u00e9es et la mise en place de mod\u00e8les pr\u00e9dictifs est aujourd\u0027hui un enjeu de soci\u00e9t\u00e9 majeur. De nombreux domaines s\u2019y int\u00e9ressent comme l\u0027industrie, la finance, la biologie. L\u2019objectif de ce cours est de maitriser les bases th\u00e9oriques et pratiques des mod\u00e8les pr\u00e9dictifs lin\u00e9aires.\u003C\/p\u003E\n\u003Cp\u003EIn English:\nThe use of data and the implementation of predictive models is now a major societal challenge. A wide range of fields such as industry, finance, biology need to use predictive models. This course aims to master the theoretical and practical foundations of linear predictive models.\u003C\/p\u003E\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EOrganisation g\u00e9n\u00e9rale et modalit\u00e9s p\u00e9dagogiques\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003E\u003Cp\u003E6 s\u00e9ances de cours de 1h45, 6 s\u00e9ances de travaux pratiques de 1h45 , 6 s\u00e9ances de projet de 1h45.\u003C\/p\u003E\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003EBibliographie\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003E\u003Cp\u003EThe Elements of Statistical Learning, T. Hasti\u00e9, R. Tibshirani, J. Friedman. Machine learning, a probabilistic perpective, K.P. Murphy Pattern recognition and machine learning, C. Bishop.\u003C\/p\u003E\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003Cdiv class=\u0022field-spacing\u0022\u003E\n \u003Cdiv class=\u0022field__label h3 dash\u0022\u003ENature de l\u0026#039;\u00e9valuation\u003C\/div\u003E\n \u003Cdiv class=\u0022mt-5 text-justify\u0022\u003E\n \u003Cspan\u003EEvaluation Continue non Int\u00e9grale\u003C\/span\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n \u003C\/div\u003E\n\u003C\/div\u003E\n","settings":null}]