amazon-sagemaker-examples and aws-ml-jp
These are ecosystem siblings: both are official AWS educational resources for SageMaker, with the first being the primary English-language example repository and the second being a Japanese-language variant covering similar machine learning workflows.
About amazon-sagemaker-examples
aws/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Covers the full ML lifecycle from data preparation through inference monitoring, with notebooks organized by workflow stage (prepare data, build/train, deploy/monitor). Introduces SageMaker-Core, a new Python SDK offering resource chaining and object-oriented abstractions over low-level SageMaker APIs, alongside traditional Boto3 patterns. Integrates with AWS primitives including managed training jobs, real-time/serverless/asynchronous endpoints, and CloudWatch-based model monitoring for drift detection.
About aws-ml-jp
aws-samples/aws-ml-jp
SageMakerで機械学習モデルを構築、学習、デプロイする方法が学べるNotebookと教材集
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