SageMaker Training

Submit ML training jobs to AWS SageMaker from the command line. Supports PyTorch, TensorFlow, scikit-learn, and XGBoost with managed spot training for cost savings.

Prerequisites

• boto3 Python package installed (pip install boto3). sagemaker recommended.
• AWS credentials available — EC2 instance profile (recommended), or aws configure / env vars (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
• S3 bucket for training artifacts
• Two IAM roles configured — see references/setup.md for exact policies:
  • Role A (Caller): SageMaker job management + S3 access + ECR image pull
  • Role B (Execution): S3 data access + CloudWatch logs + ECR images

Security Notes