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Clipping: Difference between revisions

2,833 bytes added ,  20 February 2023
Created page with "===Introduction== Clipping is a technique employed in machine learning to prevent the weights of a neural network from growing too large during optimization. Excess weights can lead to instability during training, causing the network to diverge and fail to converge on an optimal solution. ==The Need for Clipping== Machine learning algorithms like stochastic gradient descent (SGD) are commonly employed to update the weights of a neural network during training. SGD works..."
(Created page with "===Introduction== Clipping is a technique employed in machine learning to prevent the weights of a neural network from growing too large during optimization. Excess weights can lead to instability during training, causing the network to diverge and fail to converge on an optimal solution. ==The Need for Clipping== Machine learning algorithms like stochastic gradient descent (SGD) are commonly employed to update the weights of a neural network during training. SGD works...")
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