This course is part of the Mathematics for Machine Learning and Data Science Specialization by DeepLearning.AI. After completing this course, learners will be able to: Represent data as vectors and ...

Matrices are commonly used in machine learning and data science to represent data and its transformations. In this week, you will learn how matrices naturally arise from systems of equations and how ...

This course aims to develop your knowledge in the mathematics topics of linear algebra and calculus, which provides the basic mathematics foundation that is necessary for anyone pursuing a computing ...

Introduces ordinary differential equations, systems of linear equations, matrices, determinants, vector spaces, linear transformations, and systems of linear differential equations. Prereq., APPM 1360 ...

Abstract: Q (state weighting) and R (input weighting) matrices are the essential components of the linear quadratic regulator (LQR) optimization process. Trial and ...

Abstract: We consider a non-resonant system of finitely many bilinear Schrodinger equations with discrete spectrum driven by the same scalar control. We prove that this system can approximately track ...