A feature vector serves as a numerical portrayal of a collection of features or traits associated with an object or event. In the realm of machine learning, feature vectors are utilized to represent data samples in a format that algorithms can readily process.
Each element within a feature vector corresponds to an attribute or characteristic of the data sample. For example, in image recognition, a feature vector might incorporate details about the image's color, shape, and pixel values at different positions. In speech recognition, a feature vector could include the spectral characteristics of various audio frequencies over time.