BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//datacraft - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:datacraft
X-ORIGINAL-URL:https://datacraft.paris
X-WR-CALDESC:Events for datacraft
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20190331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20191027T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20200329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20201025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20200928T100000
DTEND;TZID=Europe/Paris:20200928T170000
DTSTAMP:20260430T235542
CREATED:20200910T132533Z
LAST-MODIFIED:20200928T121058Z
UID:1296-1601287200-1601312400@datacraft.paris
SUMMARY:Contribuer aux bibliothèques open source Python et à scikit-learn
DESCRIPTION:En collaboration avec l’INRIA et Scikit-learn\, datacraft vous invite à découvrir comment contribuer aux bibliothèques open source en Python et en particulier à la librairie de machine learning scikit-learn. \nWorkshop animé par Roman Yurchak\, Symerio et Guillaume Lemaître\, INRIA\, membres de l’équipe de développement de scikit-learn. \nVous aurez l’occasion de contribuer au projet scikit-learn sur Github.Nous aborderons aussi d’autres sujets tels que la collaboration sur des projets open-source engénéral. \nPour participer\, il est nécessaire de connaître Python et idéalement d’avoir utilisé scikit-learn. \n  \nLes étapes suivantes sont fortement recommandées pour préparer ce workshop: \n1. Installer Python\, par exemple en utilisant la distribution d’Anaconda \n2. Lire le guide de contribution à scikit-learn. En particulier\, suivre les étapes 1 à 6 de la section “How to contribute”.
URL:https://datacraft.paris/event/ressources-et-collaboration-sur-une-bibliotheque-open-source/
LOCATION:datacraft –\, 3 rue Rossini\, 75009 Paris\, France
ORGANIZER;CN="datacraft":MAILTO:contact@datacraft.paris
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20200921T140000
DTEND;TZID=Europe/Paris:20200921T170000
DTSTAMP:20260430T235542
CREATED:20200904T142955Z
LAST-MODIFIED:20210723T094135Z
UID:974-1600696800-1600707600@datacraft.paris
SUMMARY:Machine learning for multivariate and functional anomaly detection: ordering and data depth
DESCRIPTION:This event is organized with the participation of Pavlo Mozharovskyi\, Telecom Paris. \ndatacraft members only \nContent: \nAnomaly detection (Chandola et al.\, 2009) is a branch of machine learning which aims at identifying observations that exhibit abnormal behavior. Be it measurement errors\, disease development\, severe weather\, production quality default(s) (items) or failed equipment\, financial frauds or crisis events\, their on-time identification\, isolation and explanation constitute an important task in almost any branch of industry and science. \nDuring this workshop\, you will discuss the concept of data depth in both functional and multivariate settings\, review most common notion of the depth function (halfspace (Tukey\, 1975)\, projection (Zuo & Sefling\,2000)\, zonoid (Mosler\, 2002)\, spatial depth (Koltchinskii\, 1997); integrated (Claeskens et al.\, 2014) and curve (Lafaye De Micheaux et al.\, 2020) functional depths\, functional isolation forest Staerman et al. (2019)\, and focus on a number of real-world applications ranging from simulated situations to hurricane tracks and brain imaging. \n 
URL:https://datacraft.paris/event/machine-learning-for-multivariate-and-functional-anomaly-detection-ordering-and-data-depth/
LOCATION:datacraft –\, 3 rue Rossini\, 75009 Paris\, France
ORGANIZER;CN="datacraft":MAILTO:contact@datacraft.paris
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20200914T140000
DTEND;TZID=Europe/Paris:20200914T170000
DTSTAMP:20260430T235542
CREATED:20200828T162122Z
LAST-MODIFIED:20200925T082120Z
UID:973-1600092000-1600102800@datacraft.paris
SUMMARY:COVID-19\, fake news & AI
DESCRIPTION:This workshop aims to bring together a set of actors – data scientists\, researchers\, companies\, journalists – who have exchanged and worked during the period of containment on the issue of fake news and covid-19. \nOur collective objective was to understand\, explain and discuss the reasons for the dissemination of false\, fragmented or partial information in the media sphere and in particular in social networks. \nThis afternoon will allow them to exchange on future collaborations on this issue. \nThis event is organized with the participation of Bnf\, Buster AI\, CELSA\, CheckFirst\, datacraft\, the collective “Journistes Solidaires”\, Kap Code\, and SCAI.
URL:https://datacraft.paris/event/covid-19-fake-news-ai/
LOCATION:Online
ORGANIZER;CN="datacraft":MAILTO:contact@datacraft.paris
END:VEVENT
END:VCALENDAR