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gptkbp:instanceOf
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AWS Service Feature
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gptkbp:enables
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Machine Learning Model Training
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gptkbp:feature
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gptkb:Elastic_Inference
gptkb:CloudWatch_Metrics
Cost Optimization
Network Isolation
Custom Metrics
Hyperparameter Optimization
Automatic Model Versioning
Automatic Resource Provisioning
Automatic Stopping
Container Logs
Distributed Data Parallelism
Experiment Tracking
Managed Infrastructure
Model Checkpointing
Multi-Model Training
Scalable Compute Resources
Spot Instance Support
Training Data Encryption
Training Job Monitoring
VPC Support
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https://www.w3.org/2000/01/rdf-schema#label
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SageMaker Training
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gptkbp:integratesWith
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gptkb:Amazon_S3
gptkb:SageMaker_Debugger
gptkb:SageMaker_Experiments
gptkb:SageMaker_Model_Registry
gptkb:SageMaker_Pipelines
gptkb:AWS_Key_Management_Service
gptkb:AWS_Identity_and_Access_Management
gptkb:Amazon_CloudWatch
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gptkbp:partOf
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gptkb:Amazon_SageMaker
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gptkbp:provides
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gptkb:Amazon_Web_Services
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gptkbp:supports
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gptkb:Hugging_Face
gptkb:TensorFlow
gptkb:XGBoost
gptkb:Chainer
gptkb:MXNet
gptkb:PyTorch
gptkb:Scikit-learn
gptkb:Horovod
Custom Containers
Automatic Model Tuning
Bring Your Own Algorithm
Built-in Algorithms
Distributed Training
Managed Spot Training
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gptkbp:bfsParent
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gptkb:SageMaker_Studio_Feature_Store
gptkb:SageMaker_Studio_Model_Pipelines_Integration
gptkb:SageMaker_Feature_Store
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gptkbp:bfsLayer
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7
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