Understanding PCA using Shiny and Stack Overflow data


This is a companion discussion topic for the original entry at:

Understanding PCA using Shiny and Stack Overflow data


Principal component analysis (PCA) is a powerful approach for exploring high-dimensional data, but can be challenging for learners to comprehend. In this talk, I will walk through a practical and interactive explanation of what PCA is and how it works. As a case study I’ll explore a domain that many data analysts and data scientists are familiar with: programming languages and technologies, as understood through traffic to Stack Overflow questions. We will explore how interactive visualization using Shiny gives us insight into the complex, real-world relationships in high-dimensional datasets.

Julia Silge - Data Scientist, Stack Overflow
I love making beautiful charts, the statistical programming language R, Jane Austen, black coffee, and red wine.

Slides: Understanding PCA using Shiny and Stack Overflow data,

Julia Silge website: , Twitter:@juliasilge


This topic has been closed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.