A visual introduction to machine learning and model tuning
An interactive visual explanation of machine learning.
There are two (soon three) parts:
- A visual introduction to machine learning
- Model Tuning and the Bias-Variance Trade-off
- Coming soon
The first part focuses on exploring classification of home types based on attributes. It starts by using simple graphics of the data to communicate the concept of grouping or dividing the data, then explains how a decision tree functions and is created. The tutorial does a good job of showing the difference between training and testing data.
The second part focuses on how a model can over-fit due to natural variance.
Screenshot of a portion of the resource: