US Patent 11481620 Intelligent retraining of deep learning models utilizing hyperparameter sets

In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.