Question: Training in supervised learning involves adjusting model parameters to minimize the difference between predicted and actual labeled outputs. The model is explicitly trained to generalize

Training in supervised learning involves adjusting model parameters to minimize the difference between predicted and actual labeled outputs. The model is explicitly trained to generalize from the training data to unseen data. In k

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means, however, training is more about fitting the model to the data in a way that captures its inherent structure, with no labeled outputs guiding the process.

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