
Linear Algebra Course – Mathematics for Machine Learning and Generative AI

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A reference-style linear algebra course that covers the subject from proofs and theory through to programming and applications. Its examples draw on machine learning, computer graphics, control systems and game development.
The description presents the course as a reference rather than a short overview, with exams and solved examples included. Because the contents are extensive, check the full outline on the course page before committing.
From Matrix Calculus, To Robotics! From Control Systems, To Computer Graphics! From the Singular Value Decompositions to the Principal Component Analysis. From Systems Of Linear Equations, To Systems Of Differential Equations. From Inverses, to Pseudo Inverses. From Determinants, to positive definiteness. From Concepts To Programming. From Matlab To Python. From Proofs to Visualizations & From Theory to Applications. From Solved Examples To thoughtful Exams, and From Many Other Things to Many other things,
I, Present This Course !
My Name is Ahmed Fathy, currently a machine learning scientist at Affectiva, and a university teacher previously. Over the years, I happened to teach many subjects that make a very deep use of linear algebra. Those include Machine Learning and Deep Learning, Computer Graphics, Control Systems, Game Development, and even Pure Linear Algebra. Every one of those subjects handled linear algebra from very different perspectives. In this course, I provide them all.
This course is intended to be a Reference on linear algebra in the world of online courses, having proofs, theories, programming, concepts, applications, solved examples, visualizations, and everything ! Any suggestions for more topics to add are always welcome. Since the course contents are so large and extensive, I will not summarize them here. Instead, I ask you to please watch the promo video & also have a look on the course contents towards the bottom of the page. Have a nice day !
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