Mean Squared Error
Domain: AI Fundamentals
🎯 Motivation
A loss function for regression: average of squared differences between predictions and true values.
📋 Concrete Example
Predict house price 4.2M, actual 4.0M. Error = 0.2M. Squared = 0.04. Average over all houses gives MSE.
🔗 Analogy
Like measuring how far your darts land from the bullseye, squaring the distances so big misses hurt more.