Role of Mathematics in Machine Learning

There are four sections of mathematics that the concepts of machine learning heavily benefit from: Linear algebra, Calculus, Statistics and Probability. We shall roughly see why and when these branches of mathematics are applied during the life cycle of a machine learning model. Machine learning is most heavily dependent on linear algebra, which is used to solve simultaneous linear equations. It is done with the use of matrices and matrix operations. The data for any machine learning model is generally stored in the form of vectors and matrices, and the values contained are considered as the coefficients of the linear equations.