This repository provides example Jupyter notebooks for users of Amazon SageMaker Studio Lab, a free service for aspiring AI/ML practitioners. It offers guidance on setting up environments and developing projects in areas like computer vision, NLP, and geospatial data science, with the goal of enabling users to deploy their work on Amazon SageMaker.

How It Works

The project offers pre-built Jupyter notebooks demonstrating various AI/ML tasks. It also provides custom environment configuration files (.yml) that allow users to easily set up specific programming language and framework environments within SageMaker Studio Lab, such as R, Julia, AutoGluon, fast.ai, SciPy, Diffusers, RAPIDS, Geospatial, Medical Image AI, and Gradio.

Quick Start & Requirements

• Install/Run: Access notebooks directly via "Open in Studio Lab" buttons or clone the repository into a SageMaker Studio Lab project.
• Prerequisites: An Amazon SageMaker Studio Lab account is required to run the notebooks.
• Setup: Accessing notebooks requires no local setup. Building custom environments involves cloning the repo and following in-notebook instructions.
• Links: SageMaker Studio Lab, SageMaker Studio Lab Documentation

Highlighted Details

• Demonstrates end-to-end workflows from training to deployment on Amazon SageMaker.
• Includes examples for specialized domains like Geospatial Data Science and Medical Image AI.
• Supports custom environment creation for popular ML frameworks and languages.
• Features community-contributed examples tagged with amazon-sagemaker-lab.

Maintenance & Community

The project is maintained by AWS. Community contributions are welcomed, with guidelines provided for issues and pull requests. Links to community resources like Stack Overflow and regional forums are available.

Licensing & Compatibility

• License: Apache-2.0 License.
• Compatibility: Permissive license allows for commercial use and integration with closed-source projects.

Limitations & Caveats

The repository notes that the mechanism for accepting external contributions is still under development, which may lead to delays or closures of pull requests.