A company built a computer vision model and needs version tracking and guidance on EC2 instance types for hosting on SageMaker. They haven't hosted models on SageMaker before. Which approach provides model versioning and instance-type recommendations?

The SageMaker Model Registry is designed for versioning, managing, and deploying models, making it the appropriate choice for tracking model versions. SageMaker Inference Recommender automates the process of selecting the best instance type and configuration for deploying models, providing recommendations for optimal performance and cost, which directly addresses the need for EC2 instance type guidance. Registering the model in Amazon ECR is incorrect because ECR is for container images, not for model versioning itself. AWS Compute Optimizer provides recommendations for EC2 instances and other AWS resources but is not specifically tailored for SageMaker model deployment recommendations. SageMaker Autopilot is for automated machine learning (AutoML) and model training, not for instance type recommendations for deployment. SageMaker Experiments is for tracking and comparing training runs, not for model versioning or inference instance recommendations.