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Unsupervised Machine Learning: Principal Component Analysis and K-Means

March 6 @ 2:00 pm - 4:00 pm

Modern Languages Building (MLB), Room 2001A

This workshop will introduce participants to Principal Component Analysis (PCA) and K-Means using Python’s Scikit-learn library. We’ll introduce fundamental concepts related to machine learning (ML) and both PCA and K-Means, but the main focus of the workshop will be on using Python to solve unsupervised ML problems. Accordingly, we’ll use a couple of example datasets to demonstrate how to create and apply PCA and K-Means models using Scikit-learn. Although not required, we recommend all participants to have a basic knowledge of Python.

Details

Date:
March 6
Time:
2:00 pm - 4:00 pm
Event Category:
Event Tags:
,
Website:
http://cscar.research.umich.edu/events/category/workshops/

Organizer

CSCAR
Email:
cscar@umich.edu
Website:
cscar.research.umich.edu

Other

Prerequisite
Although not required, we recommend all participants to have a basic knowledge of Python.
U-M Affiliated Fee
0
Register
Instructors
Marcio Duarte Albasini Mourao