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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* [[AmazonSageMakerFullAccess]] | * [[AmazonSageMakerFullAccess]] | ||
* [[ScheduleConfig]] | * [[ScheduleConfig]] | ||
+ | |||
+ | == Activities == | ||
+ | * Read https://aws.amazon.com/blogs/machine-learning/train-fraudulent-payment-detection-with-amazon-sagemaker/ | ||
== See also == | == See also == |
Revision as of 10:46, 23 September 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
Activities
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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