Amazon SageMaker

wikipedia:Amazon SageMaker (Nov 2017) Machine learning service to create, train, and deploy machine-learning (ML) models in AWS.

Example IAM Policies

AmazonSageMakerFeatureStoreAccess

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:PutObject",
                "s3:DeleteObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::*"
            ]
        }
    ]
}

• Amazon SageMaker Canvas

Related

• AmazonSageMakerFullAccess
• ScheduleConfig
• Colab

Activities

• Read https://aws.amazon.com/blogs/machine-learning/train-fraudulent-payment-detection-with-amazon-sagemaker/

See also

• AWS SageMaker, aws sagemaker
• AWS ML: Amazon SageMaker, Amazon Kendra, AWS Forecast, Amazon Macie, Amazon Textract, Amazon SageMaker Canvas
• Machine learning, Deep learning, AWS Sagemaker, PyTorch, Kubeflow, TensorFlow, Keras, Torch, Spark ML, Tinygrad, Apple Neural Engine, Scikit-learn, MNIST, MLOps, AutoML, ClearML, PostgresML, AWS Batch, Transformer, Diffusion, Backpropagation, JAX, Vector database, LLM, The Forrester Wave: AI/ML Platforms

https://aws.amazon.com/about-aws/whats-new/2017/11/introducing-amazon-sagemaker/