Data Science and Machine Learning (Theory and Projects) A to Z - Gradient Descent in RNN: Chain Rule

The video tutorial explains the importance of gradients in minimizing the loss function and updating parameters. It introduces the concept of gradient calculation, particularly focusing on the derivative of the loss function with respect to WX. The tutorial further breaks down the gradient calculation using the chain rule, simplifying complex calculations into manageable parts. The application of the chain rule is demonstrated, emphasizing the simplification of gradient calculations through progressive breakdown into smaller problems.

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