{"id":162,"date":"2018-01-18T16:46:26","date_gmt":"2018-01-18T15:46:26","guid":{"rendered":"https:\/\/project.inria.fr\/rescom2018\/?page_id=162"},"modified":"2018-09-06T13:55:49","modified_gmt":"2018-09-06T11:55:49","slug":"theorie-du-data-science","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/rescom2018\/programme\/theorie-du-data-science\/","title":{"rendered":"Advanced Machine Learning and Data Science"},"content":{"rendered":"<p><img decoding=\"async\" class=\"alignright size-full wp-image-384\" src=\"https:\/\/project.inria.fr\/rescom2018\/files\/2018\/01\/andre.png\" width=\"180\" \/><\/p>\n<h3>Intervenant : <a href=\"http:\/\/andre.panisson.com\/ \">Andr\u00e9 Panisson<\/a><\/h3>\n<p>Andr\u00e9 Panisson is Principal Researcher at the Institute for Scientific Interchange in the Data Science LAB of Turin, Italy. His primary line of research examines Data Science, Complex Networks, Social Media and Urban Systems.<\/p>\n<h4>D\u00e9tail du cours<\/h4>\n<p><b>Advanced Machine Learning<\/b> and <b>Data Science<\/b><\/p>\n<ul>\n<li><b><\/b>theory of generalization<\/li>\n<li>model selection<\/li>\n<li>model validation<\/li>\n<li>cross-validation<\/li>\n<li>backtesting (hindcasting)<\/li>\n<li>forecasting.<\/li>\n<\/ul>\n<p>Data Scientists to deal with big datasets + MapReduce programming paradigm, and how it can be used with the Python language (e.g. PySpark and Dask).<\/p>\n<p>data-driven decision making and building data products with methods from recommender systems and time series analysis on image analysis<\/p>\n<p>image classification, image segmentation, object detection and transfer learning.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Intervenant : Andr\u00e9 Panisson Andr\u00e9 Panisson is Principal Researcher at the Institute for Scientific Interchange in the Data Science LAB of Turin, Italy. His primary line of research examines Data Science, Complex Networks, Social Media and Urban Systems. D\u00e9tail du cours Advanced Machine Learning and Data Science theory of generalization\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/rescom2018\/programme\/theorie-du-data-science\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":659,"featured_media":177,"parent":140,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-162","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/pages\/162","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/users\/659"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/comments?post=162"}],"version-history":[{"count":5,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/pages\/162\/revisions"}],"predecessor-version":[{"id":353,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/pages\/162\/revisions\/353"}],"up":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/pages\/140"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/media\/177"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/rescom2018\/wp-json\/wp\/v2\/media?parent=162"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}