Using Linear Algebra to solve the Machine Lea...

Using Linear Algebra to solve the Machine Learning Application

Author Name : Shaik Mubarak, Dr. Shankar Nayak Bhukya, K. Srinu

ABSTRACT

Linear algebra is a fundamental and essential component of mathematics. Mathematical structures that are closed under the operations of addition and scalar multiplication are considered part of this field of mathematics, and it contains the theories and models of systems of linear equations, matrices, determinants, vector spaces, and linear transformations as well as other branches of mathematics. It is a mathematical field that deals with vectors and matrices, and more broadly with vector spaces and linear transformations, as well as with vector spaces and linear transformations. Linear algebra, in contrast to other branches of mathematics that are constantly re-energized by new ideas and unresolved problems, is a branch of mathematics that is very well known. Its significance comes in the many applications it has, ranging from mathematical physics to contemporary algebra, as well as its application in engineering and medical areas, such as machine learning and its application. Then we demonstrate the use of linear algebra, namely matrix and vector operations, in machine learning techniques such as support vector machine and image processing.

Keywords: Linear Algebra, Linear Equations, Machine Learning, Applications.