SAGEMAKER SPACENET INSTALL
You can install the libraries needed to run the tests by running pip install -upgrade. SageMaker Python SDK has unit tests and integration tests. SageMaker Python SDK is licensed under the Apache 2.0 License. However, if you are using an IAM role with a path in it, you should grant permission for iam:GetRole. The SageMaker Python SDK should not require any additional permissions aside from what is required for using SageMaker. You can read more about which permissions are necessary in the AWS Documentation. Supported Python VersionsĪs a managed service, Amazon SageMaker performs operations on your behalf on the AWS hardware that is managed by Amazon SageMaker.Īmazon SageMaker can perform only operations that the user permits. SageMaker Python SDK supports Unix/Linux and Mac. You can install from source by cloning this repository and running a pip install command in the root directory of the repository: git clone The SageMaker Python SDK is built to PyPI and can be installed with pip as follows: pip install sagemaker SageMaker Reinforcement Learning EstimatorsĪmazon SageMaker Built-in Algorithm EstimatorsīYO Docker Containers with SageMaker EstimatorsĪmazon SageMaker Operators in Apache Airflow
If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well.įor detailed documentation, including the API reference, see Read the Docs. Which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. You can also train and deploy models with Amazon algorithms, With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow.
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.
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