amazon-sagemaker-examples and sagemaker-end-to-end-workshop
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 sagemaker-end-to-end-workshop
aws-samples/sagemaker-end-to-end-workshop
Hands-on end-to-end workshop to explore Amazon SageMaker.
This workshop helps businesses automate the identification of customers likely to churn. By using historical customer data, it trains a machine learning model to predict which current customers are at risk of leaving. The output is a prediction of customer churn, enabling proactive intervention. It is designed for data scientists and machine learning engineers looking to build and deploy customer churn prediction systems.
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