Machine Learning with R: K-means Clustering Online
Clustering is an unsupervised machine learning approach for finding subgroups of observations within a data set. This workshop will introduce participants to the theoretical part of the most common clustering method, K-means clustering. Afterwards, participants will gain hands-on experience in how to conduct K-means clustering in R, as well as how to interpret and visualize their results.
A beginner-level understanding of R-programming and introductory statistical knowledge is required for this workshop.
*Presented by Shaila Jamal (DASH Support Assistant). This virtual workshop will be recorded and shared on the Sherman Centre's website.
More information on Sherman Centre Events can be found on the SCDS Events page.
CODE OF CONDUCT
The Sherman Centre and the McMaster University Library are committed to fostering a supportive and inclusive environment for its presenters and participants. As a participant in this session, you agree to support and help cultivate an experience that is collaborative, respectful, and inclusive, as well as free of harassment, discrimination, and oppression. We reserve the right to remove participants who exhibit harassing, malicious or persistently disruptive behaviour. Please refer to our code of conduct webpage for more information.