Data Glossary Lab

Classification is a supervised learning problem when it is necessary to predict categorical outcomes based on input features. Examples of classification problems are fraud detection and email spam filters. Commonly used classification algorithms are k-nearest neighbors, decision trees, random forest, etc.

Clustering is an unsupervised learning problem concerned with grouping all the observations of a dataset according to their similarity by some common characteristics. Common clustering algorithms are k-means, hierarchical clustering, spectral clustering, etc.

Cloud Computing is the on-demand delivery of computing power, database storage, applications, and other IT resources via the internet with pay as you go pricing.

Cohort Analysis is a specialized subset of behavioral analytics that breaks down a large dataset into related groups, or "cohorts," based on shared characteristics or experiences within a specific time span. Instead of viewing all users as a single unit, this analysis tracks how specific segments behave over time, allowing businesses to identify patterns in engagement, retention, and churn.