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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