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R users gain a powerful, extensible deep learning framework with `mlr3torch`, seamlessly integrating neural networks into the familiar `mlr3` ecosystem for streamlined experimentation and deployment.
Questioning the common practice of interpreting data through a single model class, this work reveals the existence of alternative well-performing models across multiple model classes and their hyperparameters.
