Introduction to Machine Learning in R
Overview:
This tutorial aims at providing an accessible introduction to various machine learning methods and applications using the programming language R in RStudio. The core of the course focuses on supervised learning methods such as regression and classification with cross-validation.
At the end of the tutorial, participants will be able to apply what they have learnt, as well as feel confident enough to explore and apply new methods.
Prerequisites:
- Basic 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).
- Introductory knowledge of R and RStudio (basic syntax and plotting functions).
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, McGill.