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X-WR-CALNAME:Data Science Initiative
X-ORIGINAL-URL:https://datascience.uci.edu
X-WR-CALDESC:Events for Data Science Initiative
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DTSTART;TZID=America/Los_Angeles:20170203T090000
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DTSTAMP:20260405T081239
CREATED:20170117T111019Z
LAST-MODIFIED:20170117T111019Z
UID:2019-1486112400-1486141200@datascience.uci.edu
SUMMARY:Predictive Modeling with Python
DESCRIPTION:Learn about the use of predictive models in Python through scikit-learn.\n \nPython is a popular language for scientific processing and machine learning. This course will introduce general modeling concepts in addition to concrete examples based on the scikit-learn library. Example usage of scikit-learn will illustrate how to fit and evaluate predictive models. Regression and classification settings will be considered. The course will be taught mostly through the medium of iPython notebooks. \nThis course is targeted primarily at graduate students who have not already taken a full course in machine learning. \nDate: February 3\, 2017 \nTime:9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Preston Hinkle\, John Schomberg\, Brian Vegetabile\, UC Irvine \nPre-requisites: basic familiarity with Python (prior experience with scikit-learn is not necessary). To understand the more theoretical aspects of the course\, it is recommended to have knowledge of linear algebra\, probability\, and calculus. \nLearning Materials:https://github.com/UCIDataScienceInitiative/PredictiveModeling_withPython
URL:https://datascience.uci.edu/event/predictive-modeling-python-020317/
CATEGORIES:Data Science Event
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