![]() Minimum Linear Algebra for Machine Learning Linear Algebra List of Topics on Wikipedia.More information on Linear Algebra from Wikipedia: Raphael Cendrillon in answer to the question “ Why is Linear Algebra a prerequisite behind modern scientific/computational research?” ![]() ![]() Further to that most linear algebra operations can be implemented without messaging passing which makes them amenable to MapReduce implementations. Linear algebra finds widespread application because it generally parallelizes extremely well. Vignesh Natarajan in answer to the question “ How is Linear Algebra used in Machine Learning?”Īs a field, it’s useful to you because you can describe (and even execute with the right libraries) complex operations used in machine learning using the notation and formalisms from linear algebra. These linear equations are in turn represented in the form of matrices and vectors. Rather than working with scalars, we start working with matrices and vectors (vectors are really just a special type of matrix).īroadly speaking, in linear algebra data is represented in the form of linear equations. Linear Algebra is about working on linear systems of equations (linear regression is an example: y = Ax). ![]() Think of it as an extension of algebra (dealing with unknowns) into an arbitrary number of dimensions. Linear Algebra is a branch of mathematics that lets you concisely describe coordinates and interactions of planes in higher dimensions and perform operations on them.
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