# What is the Distance Between Two Vectors?

The distance between two vectors is a measure of how different they are from each other. It is a numerical value that can be calculated using a variety of methods, such as Euclidean distance, dot product, or cosine similarity.

This measure of distance is used in many machine learning and data science applications, such as clustering, classification, and recommendation systems.

For example, in a clustering algorithm, the distance between two vectors can be used to determine which cluster they should be assigned to. In a classification algorithm, the distance between two vectors can be used to determine which class they should be assigned to. In a recommendation system, the distance between two vectors can be used to determine which items should be recommended to a user.

Next Chapter:

What is the Euclidean Distance?