Projects Tagged with sagemaker — AWS SageMaker Model Training, Deployment, and MLOps Projects
Explore projects tagged with sagemaker to find real-world implementations of AWS SageMaker for end-to-end ML workflows, including model training and hyperparameter tuning, managed endpoint deployment for real-time inference, batch transforms, SageMaker Pipelines for CI/CD, and MLOps monitoring. This curated list of projects shows how teams use sagemaker for long-tail scenarios like cost-optimized distributed training on spot instances, automated model drift detection, and production-ready inference patterns; use the filtering UI to narrow results by framework (TensorFlow, PyTorch, scikit-learn), deployment pattern, dataset scale, or repository maturity. Review code samples, architecture diagrams, runtime metrics, and contributor activity to evaluate fit, then filter, compare, or clone projects to accelerate your ML deployment and productionization efforts.
