The term “Vector Databases” refers to Vector data representations are utilized by vector databases for data comprehension. Consider the scenario when you need to convert more complex data, such words, images, audio, and video, into vectors. There are various methods to measure the two vectors.
Euclidian Formula
To calculate the distance between two locations on a plane
Manhattan Formula
This is the amount of space between two vectors if you could only travel along the data’s dimensions.
Cosine Formula
This measure disregards the vectors’ length and instead looks at how similar their directions are.
DotProduct Formula
This is the length of one vector measured in the direction of the other vector
Using a certain machine learning method that relies heavily on distance measures may be the most likely scenario in which you run into distance measurements
