A Feature Vector is a numerical representation of an object, observation, or data point using a set of measurable features. It converts important characteristics into an ordered collection of numbers that machine learning algorithms can process and compare.
For example, an image-recognition system might represent an image using numerical values describing its edges, shapes, textures, and colors. These values form a feature vector that allows a model to identify similarities, classify objects, or make predictions efficiently.
