Data Science for Founders

Outlier detection is the process of identifying rare data points that deviate from the norm to help founders spot errors, fraud, or unexpected business opportunities.

Underfitting happens when a machine learning model is too simple to capture the underlying structure of data, leading to poor performance on both training and test sets.

This article explains how prescriptive analytics helps founders move beyond predicting the future to determining the most effective actions for business growth and resource optimization.

This article explains propensity modeling as a statistical tool for startups to predict customer actions like churning or upgrading using historical data and probability scores.