Educational
As data becomes more prevalent in everyone's lives, it's vital to know the basic concepts. However many people have real trouble anytime math-talk pops up. I built this app to demonstrate three of the most important concepts in all of statistics and data analysis: Mean, Variance, and Correlation. Seeing how these parameters determine the shape of data provides an intuitive, practical understanding that sidesteps technical jargon.
Probability theory is the corner stone of data science and decision making. And the cornerstone of probability theory is Bayes' Rule. An understanding of Bayes' Rule is a key to understanding how to update one's strategies based on evidence. In this project I provide a simple yet effective visualization of probability theory to show how Bayes' rule works without the formulas.
Clustering is a family of unsupervised machine learning methods that partitions data. The point is to find naturally occurring subsets of the data - carve it at its joints - you might say. In this project, I discuss the differences between three clustering methods: K-means, Gaussian Mixture Modelling, & Density Based Scanning. This includes an app that allows you to compare the clustering in real time!
