What are Vectors?

Linear Algebra for Machine Learning · Axiom Academy

Discover the power of vectors in mathematics and machine learning What do a force acting on an object, a photo's pixels, and a machine learning model all have in common? They can all be represented as vectors — ordered collections of numbers that capture magnitude and direction. Physical Forces: Vectors represent forces with both magnitude (how strong) and direction (which way). In machine learning, we use the same mathematical objects to represent data points, features, and patterns. A house can be represented as a vector with features: [2500 sqft, 4 bedrooms, 2.5 bathrooms] This vector lives in a "feature space" where each coordinate represents a property of the house. • How to represent data as vectors • Vector operations (addition, scaling, dot product) • How these operations reveal relationships between data points • How machine learning models use vectors to understand patterns

This is the written version of the interactive lesson above. See the full Linear Algebra for Machine Learning course.