Principal Component Analysis with Applications in R and Python
Introduce attendees not familiar with Principal Component Analysis (PCA) to the commonly used dimension reduction approach.
Focus on real data analysis with R and Python.
Working knowledge of statistics (e.g. correlation matrices) and linear algebra.
GitHub repository: GitHub.
Review of tutorial by Joseph Rickert (of Revolution Analytics) here.
Video excerpt from the tutorial: YouTube.
R, Python, Principal Component Analysis (PCA), Singular Value Decomposition (SVD), meetup.com, dimension reduction, ACM Data Camp 2014.