amazon-sagemaker-examples and studio-lab-examples
These are ecosystem siblings—both provide example notebooks for different SageMaker products (full SageMaker vs. the free-tier Studio Lab alternative), sharing the same underlying platform and use cases but targeting different user segments and deployment contexts.
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 studio-lab-examples
aws/studio-lab-examples
Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!
This project offers a collection of example Jupyter notebooks designed to help aspiring AI/ML practitioners learn and experiment with machine learning tasks using Amazon SageMaker Studio Lab. It provides practical demonstrations for setting up your environment and building AI/ML models in areas like computer vision, natural language processing, and generative AI. The notebooks show you how to start with raw data or pre-trained models and develop solutions for real-world problems.
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