Mathematics for Machine Learning with Python- CST284 KTU Minor - Dr. Binu V P -9847390760

Matrix Decomposition Many complex matrix operations cannot be solved efficiently or with stability using the limited precision of computers. Matrix decompositions are methods that reduce a matrix into constituent parts that make it easier to calculate more complex matrix operations. Matrix decomposition methods, also called matrix factorization methods, are a foundation of linear algebra in computers,even for basic operations such as solving systems of linear equations, calculating the inverse, and calculating the determinant of a matrix. In this tutorial, you will discover matrix decompositions and how to calculate them in Python. It is an approach that can simplify more complex matrix operations that can be performed on the decomposed matrix rather than on the original matrix itself. A common analogy for matrix decomposition is the factoring of numbers, such as the factoring of 10 into 2x5. For this reason, matrix decomposition is also called matrix factorization. Like factori