AWS SageMaker ML

AWS SageMaker is the managed ML platform covering the entire ML lifecycle: data preparation, training, hyperparameter tuning, deployment, monitoring, and retraining. Instead of managing Kubernetes clusters, writing distributed training code, and standing up model serving infrastructure, you submit a job to SageMaker, specify your compute, and it handles the rest. SageMaker includes pre-built algorithms (XGBoost, linear learner, k-means, image classification, NLP), support for open-source frameworks (TensorFlow, PyTorch, scikit-learn), and integration with popular foundation models (via Jumpstart). Deploy models to endpoints with auto-scaling, A/B testing, and production monitoring built-in.