Deep Learning CNN Convolutional Neural Networks with Python - What Is Chain Rule

The video tutorial continues from the previous lesson, focusing on derivatives and their significance in mathematical computations. It introduces the gradient descent algorithm, explaining its iterative nature and how it minimizes loss by updating values through derivatives. The tutorial also covers the chain rule, a fundamental concept in calculus, which helps in understanding how changes in one variable affect another. The video aims to provide a foundational understanding of these concepts, preparing viewers for more complex applications in neural networks.

What is meant by the 'loss function' in the context of this video?

What steps are involved in computing the derivative of the loss function with respect to K?

How does the derivative with respect to a variable measure its effect on the loss function?