Answer Posted / Himanshu Kumar Pandey

Tuning in Machine Learning (ML) refers to adjusting the hyperparameters of an algorithm to optimize its performance. Hyperparameters are parameters that are set before the learning process begins and are not learned from data. Examples include learning rate, regularization strength, and number of layers in a neural network.

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