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  • Using the SageMaker Python SDK
  • Use Version 2.x of the SageMaker Python SDK
  • APIs
    • Feature Store APIs
    • Training APIs
    • Distributed Training APIs
    • Inference APIs
    • Governance APIs
    • Utility APIs
  • Frameworks
  • Built-in Algorithms
  • Workflows
  • Amazon SageMaker Experiments
  • Amazon SageMaker Debugger
  • Amazon SageMaker Feature Store
  • Amazon SageMaker Model Monitor
  • Amazon SageMaker Processing
  • Amazon SageMaker Model Building Pipeline
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APIsΒΆ

The SageMaker Python SDK consists of a variety classes for preparing data, training, inference and general utility:

  • Feature Store APIs
    • Feature group
    • Feature definition
    • Inputs
    • Dataset Builder
  • Training APIs
    • Analytics
    • AutoML
    • Debugger
    • Estimators
    • Algorithm Estimator
    • HyperparameterTuner
    • Parameters
    • Processing
  • Distributed Training APIs
    • The SageMaker Distributed Data Parallel Library
    • The SageMaker Distributed Model Parallel Library
  • Inference APIs
    • Async Inference
    • Deserializers
    • Model
    • Model Monitor
    • MultiDataModel
    • PipelineModel
    • AsyncPredictor
    • Predictors
    • Serializers
    • Serverless Inference
    • Transformer
  • Governance APIs
    • Amazon SageMaker Model Cards
  • Utility APIs
    • Environment Variables
    • Hyperparameters
    • Image URIs
    • Inputs
    • Instance Group
    • Lambda Utilities
    • Model URIs
    • Network Configuration
    • S3 Utilities
    • Script URIs
    • Session
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