Gradient clipping in DL

Gradient clipping is a technique commonly used in deep / machine learning, particularly in the training of deep neural networks, to address the issue of exploding gradients.

Exploding gradients occur when the gradients of the loss function with respect to the model's parameters become very large during training. This can lead to numerical instability and make it challenging for the model to converge.

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