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What is hyper-parameter tuning?

Hyper-Parameter Tuning

When creating a machine learning model, we have to define our model architecture. Oftentimes, we don’t immediately know what the optimal model architecture should be for a given model, and thus we’d like to be able to explore a range of possibilities. In true machine learning fashion, we’ll ideally ask the machine to perform this exploration and select the optimal model architecture automatically. Parameters that define the model architecture are referred to as hyperparameters and thus this process of searching for the ideal model architecture is referred to as hyperparameter tuning.