Spoilers

Explore the fundamental steps of gradient descent including initialization, forward pass, loss calculation, and parameter updates using a simple linear regression model in Numpy. Understand different gradient descent techniques, effects of learning rates, and the importance of feature scaling, setting a solid foundation before applying PyTorch.