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.
This project provides a collection of example Jupyter notebooks that show you how to use Amazon SageMaker for your machine learning projects. These notebooks walk you through the entire machine learning workflow, from preparing data to building, training, deploying, and monitoring models. Data scientists, machine learning engineers, and researchers can use these examples to learn how to operationalize their ML models on AWS.
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
This collection of tutorials helps you build, train, and deploy machine learning models on AWS. It provides practical examples and guided lessons, showing you how to turn raw data into predictive models and integrate them into real-world applications. Data scientists, machine learning engineers, and application developers who want to leverage AWS for their ML projects will find this useful.
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