Amazon SageMaker Python SDK¶
Amazon SageMaker Python SDK is an open source library for training and deploying machine-learned models on Amazon SageMaker.
With the SDK, you can train and deploy models using popular deep learning frameworks, algorithms provided by Amazon, or your own algorithms built into SageMaker-compatible Docker images.
Here you’ll find API docs for SageMaker Python SDK. The project homepage is in Github: https://github.com/aws/sagemaker-python-sdk, where you can find the SDK source, installation instructions and a general overview of the library.
The SageMaker Python SDK consists of a few primary interfaces:
A managed environment for MXNet training and hosting on Amazon SageMaker
A managed environment for TensorFlow training and hosting on Amazon SageMaker
A managed enrionment for Scikit-learn training and hosting on Amazon SageMaker
A managed environment for PyTorch training and hosting on Amazon SageMaker
A managed environment for Chainer training and hosting on Amazon SageMaker
A managed environment for Reinforcement Learning training and hosting on Amazon SageMaker
A managed environment for SparkML hosting on Amazon SageMaker
SageMaker First-Party Algorithms¶
Amazon provides implementations of some common machine learning algortithms optimized for GPU architecture and massive datasets.
SageMaker APIs to export configurations for creating and managing Airflow workflows.