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CALSCALE:GREGORIAN
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X-WR-TIMEZONE:America/Los_Angeles
X-PUBLISHED-TTL:PT15M
BEGIN:VEVENT
DTSTART:20220617T170000Z
DTEND:20220617T200000Z
DTSTAMP:20220617T000000Z
SUMMARY:Machine Learning: Document Topic Modeling
DESCRIPTION:Overview\n\nThis workshop will introduce unsupervised machine 
 learning through topic modeling. Participants will use scikit-learn to 
 identify topic clusters in a collection of documents. Through hands-on 
 programming exercises\, we will investigate using ML algorithms such as 
 k-means clustering to 1) categorized documents into different clusters and 
 2) analyze the voculabulary (words and terms) most frequent in each 
 cluster. \n\nThis workshop will take place online over UCSF Zoom. 
 Registered participants will recieve an email through LibCal with 
 connection information the day before the 
 workshop.\n\nPrerequisites\n\nFamiliarity with Python.\n\nInstructor 
 \n\nGeoffrey Boushey with the UCSF Library Data Science Initiative
ORGANIZER;CN="Geoffrey Boushey":MAILTO:Geoffrey.Boushey@ucsf.edu
CATEGORIES:Programming
CONTACT;CN="Geoffrey Boushey":MAILTO:Geoffrey.Boushey@ucsf.edu
STATUS:CONFIRMED
UID:LibCal-9238065
URL:https://calendars.library.ucsf.edu/event/9238065
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DESCRIPTION:Reminder
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