Lectures related to Stochastic Gradient Descent: Non-convex Optimization Techniques

Explores gradient descent, loss functions, and optimization techniques in neural network training.

Explores the optimality of convergence rate in gradient descent and acceleration techniques for convex and non-convex problems.

Introduces optimization basics, covering logistic regression, derivatives, convex functions, gradient descent, and second-order methods.