sagemaker
v2.106.0
  • Using the SageMaker Python SDK
  • Use Version 2.x of the SageMaker Python SDK
  • APIs
  • Frameworks
    • Apache MXNet
    • Chainer
    • Hugging Face
    • PyTorch
    • Reinforcement Learning
    • Scikit-Learn
    • SparkML Serving
    • TensorFlow
    • XGBoost
  • Built-in Algorithms
  • Workflows
  • Amazon SageMaker Debugger
  • Amazon SageMaker Feature Store
  • Amazon SageMaker Model Monitor
  • Amazon SageMaker Processing
  • Amazon SageMaker Model Building Pipeline
sagemaker
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FrameworksΒΆ

The SageMaker Python SDK supports managed training and inference for a variety of machine learning frameworks:

  • Apache MXNet
    • Use MXNet with the SageMaker Python SDK
    • MXNet Classes
  • Chainer
    • Using Chainer with the SageMaker Python SDK
    • Chainer
  • Hugging Face
    • Hugging Face
    • Train Hugging Face models on Amazon SageMaker with the SageMaker Python SDK
    • Deploy Hugging Face models to Amazon SageMaker with the SageMaker Python SDK
  • PyTorch
    • PyTorch
    • Use PyTorch with the SageMaker Python SDK
  • Reinforcement Learning
    • Using Reinforcement Learning with the SageMaker Python SDK
    • RLEstimator
  • Scikit-Learn
    • Using Scikit-learn with the SageMaker Python SDK
    • Scikit Learn
  • SparkML Serving
    • SparkML Serving
  • TensorFlow
    • Use TensorFlow with the SageMaker Python SDK
    • Deploying to TensorFlow Serving Endpoints
    • Upgrade from Legacy TensorFlow Support
    • TensorFlow
  • XGBoost
    • Use XGBoost with the SageMaker Python SDK
    • XGBoost Classes for Open Source Version
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