Dot product
Multiplies two vectors into a single number that measures how much they point the same way. It is positive when they broadly agree, zero when they are perpendicular, and negative when they oppose — which is why almost every similarity score in machine learning starts here.
- The first vector.
- The second vector, of the same length.
- The angle between them.