What are Hyperparameters, and why are they so important to A.I.?
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The parameters of an AI model are the gargantuan tables of numbers that make up the calculations of the model and which are refined during model training.
The hyperparameters of a model are the decisions made in advance of any training, like how many layers the model should have, how many numbers should be used per layer, how many numbers should be used to represent a word, how quickly the values of these numbers should change during each phase of training, and so on. They are chosen up front by humans, not refined through training.
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