Lectures related to Vectors and Tensors: Derivatives and Transformations

Covers the analysis of scalar fields, including divergence, gradient, and Laplacian.

Introduces differential operators, gradient, and divergence in vector fields.

Covers the concept of Green function and Laplacian formulas in mathematics.

Covers vector calculus concepts like gradient, divergence, and curl with applications in physics and engineering.

Explores the optimization of neural networks using Stochastic Gradient Descent (SGD) and the concept of dual risk versus empirical risk.

Covers vector fields, gradient, divergence, heat flux, and stress tensors.

Explores Green's theorem, vector field curl, Ampère's law, and magnetic field modeling.