OPTIMIZERS EXPLAINED

Understanding optimizers is essential if you want to truly master deep learning. In this video, we break down the core optimization algorithms used to train neural networks and transformer models: Gradient Descent (GD), Stochastic Gradient Descent (SGD), Momentum, RMSprop, and Adam. Before we dive into Adam and AdamW in the next video, this episode gives you the complete foundation you need to understand how models actually learn. You’ll learn: • Why optimization is necessary in deep learning • How gradient descent works mathematically • The difference between GD and SGD • Why Momentum hel…