Vector normalization is a mathematical operation that scales a vector to have a length of 1. This is often done to make vectors comparable to each other, or to ensure that they are within a specific range.
Vector normalization is important in a variety of applications, including computer graphics, machine learning, and physics. In computer graphics, normalization is used to ensure that vectors representing light and surface normals are of equal length. In machine learning, normalization is used to ensure that input data is on the same scale, which can improve the accuracy of models. In physics, normalization is used to ensure that vectors representing physical quantities, such as velocity and force, are of equal magnitude.
