Introduction to Machine Learning in R
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Overview:
ThisÌýtutorial aims at providing an accessible introduction to various machine learning methods and applications usingÌýthe programming languageÌýR in RStudio. The core of the course focuses onÌýsupervised learning methodsÌýsuch as regressionÌýand classification with cross-validation.
At the end of the tutorial,Ìýparticipants willÌýbe able to apply what they have learnt, as well as feel confident enough to explore and apply new methods.
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Ìý Ìý Ìý -ÌýBasic knowledge of statistics: descriptive statistics (mean, median, mode, variance and standard deviation), probability (distributions, conditional probability), inferential statistics (hypothesis testing, confidence interval) and regression analysis (simple linear regression and multiple regression).
Ìý Ìý Ìý -ÌýIntroductory knowledge of R and RStudio (basic syntax and plotting functions).Ìý
Date: Wednesday, 29 March 2023.
Time: 12:30 p.m. to 2:30 p.m.
Location: hybrid (in-person at Burnside Hall 1104, and online via Zoom).
Instructor: Peng Tang, PhD student, Department of Mathematics&Statistics, Æ»¹ûÒùÔº.
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