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Mathematics is an essential toolset for data scientists. By mastering these mathematical concepts, data scientists can better understand the underlying mechanisms of machine learning algorithms, improve their ability to clean and manipulate data, and make more accurate predictions and decisions based on data. Matlab has functions that allow easy work in Linear Algebra. In this book, typical algebra topics are developed, such as work in discrete mathematics through numerical algebra in the real and complex fields. Work with algebraic expressions, polynomials, equations, systems of equations, matrices, vector spaces, linear maps, and quadratic forms is presented. Matrix algebra is specially developed with advanced treatment of eigenvalues, eigenvectors and diagonalization. He also delves into drawing curves and surfaces in explicit, implicit, parametric, and polar coordinates. The concepts are accompanied by examples solved step by step with Matlab
