[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”3.22″][et_pb_row _builder_version=”3.22.1″ border_color_all=”#3255c9″ border_style_all=”groove”][et_pb_column type=”1_4″ _builder_version=”3.22.1″][et_pb_text _builder_version=”3.22.1″ min_height=”11px” custom_margin=”||-25px|||” custom_padding=”||0px|||”]<\/p>\n
Foula Vagena<\/strong> <\/p>\n [\/et_pb_text][\/et_pb_column][et_pb_column type=”3_4″ _builder_version=”3.22.1″][et_pb_text _builder_version=”3.22.1″ custom_margin=”|||||” custom_padding=”0px|||||”]<\/p>\n Data science is the area of study which involves extracting insights from data using various scientific methods, algorithms, and processes. In this tutorial we will explain the need for data science and provide an overview of the field, its main components, the opportunities that it creates as well as its major challenges. We will then describe the main steps of performing data science starting from an analytics problem up to the point of communicating the results. We will then summarize applications where data science has traditionally been employed and provide examples of data science popular tools. The tutorial will conclude with an illustrative hands-on example of the data science process. 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In this tutorial we will explain the need for data science and provide an overview of the field, its main components, the opportunities that it creates as well as… Lire la suite Foula Vagena – Data Science: A high level overview<\/span><\/a><\/p>\n","protected":false},"author":560,"featured_media":2985,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[57,1,67],"tags":[],"class_list":["post-2981","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-57","category-diip","category-seminars-hands-on-workshops"],"_links":{"self":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2981","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/users\/560"}],"replies":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/comments?post=2981"}],"version-history":[{"count":5,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2981\/revisions"}],"predecessor-version":[{"id":3088,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/posts\/2981\/revisions\/3088"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media\/2985"}],"wp:attachment":[{"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/media?parent=2981"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/categories?post=2981"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wordpress-test.app.u-pariscite.fr\/diip\/wp-json\/wp\/v2\/tags?post=2981"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
April 7, 4pm
online (zoom)<\/span><\/p>\nAbstract<\/strong><\/h3>\n
The hands-on workshop will focus on Image Analysis + Segmentation using a pre-trained Mask R-CNN model.<\/p>\n
(Universit\u00e9 Paris Cit\u00e9, diiP)
Zografoula Vagena is a research associate at the Data Intelligence Institute of Paris (diiP) and affiliated with the Universit\u00e9 Paris Cit\u00e9. She has been a data science researcher and practitioner for over ten years. She has worked on different analytics problems including forecasting, image processing, graph analytics, multidimensional data analysis, text processing, recommendation systems, sequential data analysis and optimization within various fields such as transportation, healthcare, retail, finance\/insurance and accounting. She has also performed research in the intersection of data management and analytics, and was a primary contributor of the MCDB\/SimSQL systems that blended data management with Bayesian statistics. She holds a PhD in data management from the University of California, Riverside.
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\n[\/et_pb_button][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”3.22.1″][et_pb_column type=”1_4″ _builder_version=”3.22.1″][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”3.22.1″][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”3.22.1″][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”3.22.1″][et_pb_row custom_margin=”120px||” _builder_version=”3.22.1″ locked=”off”][et_pb_column type=”4_4″ _builder_version=”3.0.47″][et_pb_divider _builder_version=”3.22.1″][\/et_pb_divider][et_pb_text admin_label=”\u00c0 lire aussi” _builder_version=”3.22.1″ z_index_tablet=”500″]<\/p>\nOther seminars
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