Optimization
Optimization finds model parameters or decisions that best satisfy an objective while respecting practical resource and safety constraints.
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Optimization finds model parameters or decisions that best satisfy an objective while respecting practical resource and safety constraints.
Hyperparameter tuning searches for training and model settings that deliver strong performance on validation data.
A preset configuration that determines how a machine learning model learns from data. Adjusting hyperparameters like learning rate and depth helps optimize performance and model accuracy.