Lectures related to Kernel (linear algebra)

Delves into singular value decomposition and its applications in linear algebra.

Explores particle interactions, forces, Newton's laws, and the center of mass in systems.

Covers the basics of electrotechnique, including linear elements, regimes, power types, and practical applications.

Introduces Python modules and NumPy for efficient array operations and linear algebra in data science.

Covers orthogonal linear maps, orthogonal matrices, invertibility, and least squares solutions in Euclidean spaces.

Covers vector spaces, bases, and dimensions, exploring key concepts for solving systems of equations.