{"id":200,"date":"2019-07-11T16:22:33","date_gmt":"2019-07-11T14:22:33","guid":{"rendered":"https:\/\/project.inria.fr\/dirtydata\/?p=200"},"modified":"2019-07-11T16:22:33","modified_gmt":"2019-07-11T14:22:33","slug":"presentation-useful-results-from-dirtydata-for-machine-learning-in-python-on-non-curated-data","status":"publish","type":"post","link":"https:\/\/project.inria.fr\/dirtydata\/presentation-useful-results-from-dirtydata-for-machine-learning-in-python-on-non-curated-data\/","title":{"rendered":"Presentation: Useful results from DirtyData for machine learning in Python on non-curated data"},"content":{"rendered":"<p>A presentation on practical results from the DirtyData project for data analysts that run machine learning in Python on non-curated data<\/p>\n<p><iframe loading=\"lazy\" style=\"border: 1px solid #CCC; border-width: 1px; margin-bottom: 5px; max-width: 100%;\" src=\"\/\/www.slideshare.net\/slideshow\/embed_code\/key\/6pszeuKlJIV0OP\" width=\"595\" height=\"485\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" allowfullscreen=\"allowfullscreen\"> <\/iframe><\/p>\n<div style=\"margin-bottom: 5px;\"><strong> <a title=\"Machine learning on non curated data \" href=\"\/\/www.slideshare.net\/GaelVaroquaux\/machine-learning-on-non-curated-data-154905090\" target=\"_blank\" rel=\"noopener\">Machine learning on non curated data <\/a> <\/strong> from <strong><a href=\"https:\/\/www.slideshare.net\/GaelVaroquaux\" target=\"_blank\" rel=\"noopener\">Gael Varoquaux<\/a><\/strong><\/div>\n","protected":false},"excerpt":{"rendered":"<p>A presentation on practical results from the DirtyData project for data analysts that run machine learning in Python on non-curated data Machine learning on non curated data from Gael Varoquaux<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/dirtydata\/presentation-useful-results-from-dirtydata-for-machine-learning-in-python-on-non-curated-data\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1155,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-200","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/posts\/200","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/users\/1155"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/comments?post=200"}],"version-history":[{"count":3,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/posts\/200\/revisions"}],"predecessor-version":[{"id":203,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/posts\/200\/revisions\/203"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/media?parent=200"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/categories?post=200"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/project.inria.fr\/dirtydata\/wp-json\/wp\/v2\/tags?post=200"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}