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X-ORIGINAL-URL:https://datascience.uci.edu
X-WR-CALDESC:Events for Data Science Initiative
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DTSTART;TZID=America/Los_Angeles:20171013T090000
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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: October 13\, 2017 \nTime: 9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Preston Hinkle\, John Schomberg\, 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-2/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=image/png:https://datascience.uci.edu/wp-content/uploads/2014/09/python_2.png
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DTSTART;TZID=America/Los_Angeles:20171020T090000
DTEND;TZID=America/Los_Angeles:20171020T170000
DTSTAMP:20260404T211809
CREATED:20170928T151625Z
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UID:2262-1508490000-1508518800@datascience.uci.edu
SUMMARY:Intro to Data Analysis with R
DESCRIPTION:This course provides an introduction to fundamentals of data analysis using the R language.\n \nIn this course\, you will learn how to effectively use R for data analysis. This course provides a brief introduction to the fundamentals of the R language and focuses on its use for data analysis–including exploratory data analysis\, linear and logistic regression\, variable selection\, model diagnostics\, and prediction. Practical examples will be provided during the course. \nDate: October 20\, 2017 \nTime: 9 a.m. to 5 p.m. with lunch provided \nLocation: Donald Bren Hall\, Room 4011 \nInstructor: Emma Smith\, Chris Galbraith\, UC Irvine \nPre-requisites: 1) familiarity with basic statistical concepts\, and 2) basic programming knowledge. For the tutorial\, bring a laptop with R downloaded and installed and WiFi. \nTeaching material repository:https://github.com/UCIDataScienceInitiative/IDA-with-R
URL:https://datascience.uci.edu/event/intro-data-analysis-r/
CATEGORIES:Data Science Event
ATTACH;FMTTYPE=image/jpeg:https://datascience.uci.edu/wp-content/uploads/2014/09/r-project-logo.jpg
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