Learning Path

Multivariable Calculus → Optimization in Deep Learning

This advanced learning path provides a systematic and rigorous treatment of optimization algorithms used in machine learning, covering gradient descent variants, momentum, adaptive methods, learning rate schedules, convergence analysis, and constrained optimization. It builds on calculus and linear algebra foundations to develop both theoretical understanding and practical insight for training ML models effectively.