What is Regularization: Bias-Variance Tradeoff

Good practice to improve the prediction with unseen data

Photo by Markus Winkler on Unsplash

When we talk about prediction using machine learning models, it’s important to understand prediction errors (i.e., bias and variance). The goal of any machine learning model is to find a model that minimizes the prediction errors on unseen data. There’s a tradeoff of a model’s ability to…