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gptkbp:instanceOf
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machine learning workflow service
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gptkbp:developedBy
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gptkb:Amazon
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gptkbp:documentation
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https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines.html
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gptkbp:enables
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automation of ML model building
automation of ML model deployment
automation of ML model training
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gptkbp:features
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encryption in transit
encryption at rest
IAM integration
VPC support
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https://www.w3.org/2000/01/rdf-schema#label
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SageMaker Pipelines
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gptkbp:integratesWith
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gptkb:AWS_Step_Functions
gptkb:Amazon_S3
gptkb:Amazon_SNS
gptkb:Amazon_SQS
gptkb:Amazon_ECR
gptkb:AWS_Lambda
gptkb:Amazon_CloudWatch
gptkb:Amazon_SageMaker_Studio
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gptkbp:launchDate
|
2020
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gptkbp:partOf
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gptkb:Amazon_SageMaker
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gptkbp:priceRange
|
pay-as-you-go
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gptkbp:regionAvailability
|
AWS global
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gptkbp:relatedTo
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gptkb:Amazon_SageMaker_Deployment
gptkb:Amazon_SageMaker_Experiments
gptkb:Amazon_SageMaker_Model_Registry
gptkb:Amazon_SageMaker_Processing
gptkb:Amazon_SageMaker_Training
gptkb:Amazon_SageMaker_Tuning
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gptkbp:supports
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gptkb:Python_SDK
gptkb:model
data lineage tracking
custom containers
callback steps
conditional steps
custom algorithms
end-to-end machine learning workflows
pipeline execution history
pipeline parameters
step caching
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gptkbp:uses
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data preprocessing
model deployment
model evaluation
model monitoring
model registration
automated ML model retraining
continuous integration and deployment for ML
feature engineering automation
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gptkbp:bfsParent
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gptkb:AWS_SageMaker
gptkb:SageMaker_Clarify
gptkb:SageMaker
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gptkbp:bfsLayer
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6
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