In machine learning, weights are parameters within a model that determine the strength of the connection between neurons in a neural network. They are crucial for learning patterns from data, as they adjust during training to minimize the difference between the model’s predictions and the actual outcomes. Proper weight initialization and adjustment are essential for effective model training and performance.
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