Deep Learning CNN Convolutional Neural Networks with Python - Implementation in NumPy BackwardPass 4

This video tutorial covers the computation of derivatives with respect to parameters C and K, essential for calculating the loss function's derivative. It begins with a recap of previous concepts and introduces the necessary formulas. The tutorial then demonstrates the implementation of these computations in code, focusing on the use of the chain rule and handling boundary conditions. The video concludes with the finalization of the derivative computation with respect to K, setting the stage for future discussions on parameter B.

What are the steps involved in implementing the derivative computation in code?

Explain how the function for computing the derivative is structured.

What is the significance of the indices I, U, J, and V in the computation?

What will be the next topic discussed in the following video?