Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

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Engines Podcast The Engines of Our Ingenuity 2514: Linear Algebra and Netflix Episode: 2514 How Netflix uses linear algebra to determine what movies you will like best. Today, UH math professor Krešo ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations ...

Abstract: A system-on-chip (SoC) photonic-electronic linear-algebra accelerator with the features of wavelength-division-multiplexing (WDM) based broadband photodetections and high-dimensional ...

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. They are a crucial part of linear algebra and have various applications in fields like engineering, ...

MAL111 - Mathematics Laboratory MATLAB Codes. Bisection Method, Fixed Point Method, Gauss Elimination, Gauss Jordan, Matrix Inversion, Lagrange Interpolation, Newton-Raphson, Regula-Falsi, Row Reduced ...

My bookshelves are lined with materials that support my work in data science and machine learning. I have a large section of mathematics books including several on the subject of linear algebra. For ...