Eigen and Pybind Libraries

Related lectures (22)

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Explores linear algebra basics, emphasizing matrix representations of transformations and the importance of choosing appropriate bases.

Explores dynamic memory allocation in C, covering malloc, calloc, and realloc functions, emphasizing proper memory management and dynamic arrays.

Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.

Explains linear independence, bases, and dimension in vector spaces, including the importance of the order of vectors in a basis.

Covers the concept of expressing vectors in proper bases and the importance of diagonalization of matrices.

Explores linear algebra over integers, emphasizing solutions to A.x=b equations and Hermite normal form.

Explores landmarks, coordinates, vectors, coplanarity, Cartesian equations, and geometric rules in space.

Covers linear transformations using matrices, focusing on linearity, image, and kernel.

Explores the application of Schur's Lemmas in physics, emphasizing operator properties and vector actions.