> One common application is the Dot Product , which is a fancy way of taking two N Dimension vectors and measuring how close those vectors point in the same dir

> One common application is the Dot Product , which is a fancy way of taking two N Dimension vectors and measuring how close those vectors point in the same direction in a [1, 1] range. That's cosine similarity, or normalised dot product. The dot product can take any value when the vectors are not unit norm.