Spell - Hyperparameter Searches

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Optimize hyperparameters to improve the accuracy of your model with the Spell Hyper command

A hyperparameter is a high-level property of a machine learning model that typically governs the training process itself (e.g., learning rate, number of hidden layers in a neural network). Thus, a hyperparameter cannot generally be optimized with a single training of the model. Rather, the same model must be trained numerous times while varying the hyperparameter values to determine optimal values. Spell implements a number of features to help you automate this process. The spell hyper command kicks off your hyperparameter search. You can choose between a grid search, random search, or bayesian search. Learn more at: https://spell.run/docs/hyper_searches

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Spell
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