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This document discusses the role of the chain rule in gradient computation during backpropagation in deep neural networks, highlighting its importance for efficient training. It outlines the process of backpropagation, the application of the chain rule, and the challenges faced in gradient computation. The conclusion emphasizes that the chain rule is essential for training deep models effectively, despite challenges like vanishing gradients.
- Author
- sadhanaarumugam07
- Language
- EN