Linear Algebra

Advanced mathematics and its applications such as machine learning (ML) or optimization would be too simple, ineffective, and quite frankly dull, if we could only work on univariate problems. Linear algebra provides the data-types, the tools, the operations, and the theory to enable the use of multivariate datasets and multivariate models.

This article presents an overview of concepts from linear algebra that are essential to achieving mastery in machine learning, deep learning, optimization, and multivariate calculus.


To build a strong foundation for advanced material such as machine learning, deep learning, statistics, and reinforcement learning, we recommend familiarity with these concepts in linear Algebra. Follow the links to our deep-dive articles to become an expert.

Further reading and resources

Here are some additional resources on linear algebra to supplement the material presented here.

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