Linear Algebra for Machine Learning: Critical Concepts

Linear algebra is a branch of mathematics that deals with vectors, matrices, and linear transforms, and it plays an important role in Machine Learning algorithms, data analysis, and classification, among other areas. Machine Learning is used to give computers the ability to learn and make decisions on their own, a field that shares many similarities with mathematics, especially Linear Algebra, which is utilized in areas such as graphing, prediction, and regression. In this work, we examine the relationship between linear algebra and machine learning, and we provide a quick introduction to certain statistical ideas because this field is so inextricably linked to mathematics and statistics. Finally, we demonstrate how linear algebra, namely matrices and vectors, are used in popular machine learning methods like linear regression and support vector machine.