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authorLexi Winter <ivy@FreeBSD.org>2025-12-01 03:19:41 +0000
committerLexi Winter <ivy@FreeBSD.org>2025-12-01 03:19:41 +0000
commit2e80774d0b20d167bc0a9e2b63dafbfb171c0d22 (patch)
tree25f0138e1af8902b92dacc8cce09b267447c17db /misc/py-sagemaker-core/pkg-descr
parentf85f2b2d6e5b7ed869376eb4b180c3a74a5c5da9 (diff)
parent1a30da80670973368b399f2b01fe9c04b91a1273 (diff)
Merge remote-tracking branch 'freebsd/main' into lf/mainlf/main
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diff --git a/misc/py-sagemaker-core/pkg-descr b/misc/py-sagemaker-core/pkg-descr
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-sagemaker-core is a Python SDK designed to provide an object-oriented interface
-for interacting with Amazon SageMaker resources. It offers full parity with
-SageMaker APIs, allowing developers to leverage all SageMaker capabilities
-directly through the SDK. sagemaker-core introduces features such as dedicated
-resource classes, resource chaining, auto code completion, comprehensive
-documentation and type hints to enhance the developer experience as well as
-productivity.
+sagemaker-core is a part of the SageMaker Python SDK.
+
+SageMaker Python SDK is an open source library for training and deploying
+machine learning models on Amazon SageMaker.
+
+With the SDK, you can train and deploy models using popular deep learning
+frameworks Apache MXNet and TensorFlow. You can also train and deploy
+models with Amazon algorithms, which are scalable implementations of core
+machine learning algorithms that are optimized for SageMaker and GPU training.
+If you have your own algorithms built into SageMaker compatible Docker
+containers, you can train and host models using these as well.