<ul><li>In a neural network, weights control the strength of the connections between neurons and are adjusted during training to minimize error and learn patterns.</li><li>Weights determine the influence of inputs on neurons and define information flow in a network.</li><li>Backpropagation is the algorithm used to update weights by propagating error through the network.</li><li>The weights are updated by computing the gradient of the loss function and adjusting them in the direction that decreases the loss.</li></ul>

Weight in Neural Network

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