The most important distinction in data is between structured and unstructured. A table has rows, columns, and a rigid format that makes patterns easy to analyze and outputs easier to explain. An image, a document, or an audio file has none of that—its meaning lives in the arrangement of pixels or the sequence of words.

In this video, you'll learn how each type maps to a model family: XGBoost for tables, convolutional neural networks for images, large language models for text. You'll also meet the in-between case, networks and graphs, and the specialized models built to work with relationships.