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A Crash Course on Linear Algebra — Part 1
Linear algebra is a powerful toolkit for simultaneously dealing with relationships and transformations involving multiple quantities. Whether you’re managing a portfolio in finance, building a machine learning model, or simply solving a set of equations, linear algebra gives you the tools to do it efficiently. It’s like the “language” that helps computers and mathematicians talk about and solve complex problems involving many variables at once.
In finance and data science, linear algebra allows us to make sense of and make decisions based on vast amounts of data. It’s everywhere in these fields, even if we don’t always see it. Whether optimizing investments, predicting trends, or encrypting data, linear algebra is the silent workhorse that makes it all possible.
History
Linear algebra’s history spans from ancient methods of solving equations to modern computing and data science applications. It evolved from basic algebraic methods and geometric ideas into a formalized and essential branch of mathematics, with profound applications across science, engineering, and technology.
The origins of linear algebra can be traced back to the ancient Babylonians, who developed methods to solve systems of linear equations, particularly in two variables. Their approach was mostly algebraic and…
