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A healthcare research organization is running ML models on-premises to analyze patient data for early disease detection. The organization uses custom Python scripts written with PyTorch and relies on proprietary medical datasets for training the models. The models are highly customized and require domain-specific knowledge for accurate predictions. The organization plans to migrate the ML workflows to AWS to leverage scalable and managed infrastructure. The migration must require the least effort while ensuring minimal changes to the existing PyTorch scripts. What do you recommend?