Difference between revisions of "Amazon SageMaker"
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↑ https://aws.amazon.com/about-aws/whats-new/2017/11/introducing-amazon-sagemaker/
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[[Machine learning]] service to create, train, and deploy machine-learning (ML) models in AWS. | [[Machine learning]] service to create, train, and deploy machine-learning (ML) models in AWS. | ||
− | == Example == | + | == Example IAM Policies == |
<code>[[AmazonSageMakerFeatureStoreAccess]]</code> | <code>[[AmazonSageMakerFeatureStoreAccess]]</code> | ||
{ | { |
Revision as of 10:36, 2 May 2022
wikipedia:Amazon SageMaker (Nov 2017) [1] 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:::*" ] } ] }
Related
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
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