/studio-lab-examples

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

SageMaker Studio Lab Examples

Example Jupyter notebooks that demonstrate how to build AI/ML learning environment using Amazon SageMaker Studio Lab.

📚 Background

SageMaker Studio Lab is a service for individual data scientist who wants to develop the career toward AI/ML practitioner. You can start your ML journey for free.

This repository introduces you to the way to set up Studio Lab according to your interest area, such as computer vision, natural language processing, etc. And also, we show how to deploy your project to the Amazon SageMaker to become the AI/ML practitioner.

🛠️ Setup

Please follow the Onboard to Amazon SageMaker Studio Lab.

  1. Request a Studio Lab account
  2. Create a Studio Lab account
  3. Sign in to Studio Lab

💻 Usage

There are 2 ways to use examples.

  1. Read: You can read the notebook in Studio Lab without Studio Lab account. Please feel free to push Open in Studio Lab button in Examples section.
  2. Run: You can run the notebook by copying the notebook or git clone the repository to your Studio Lab project.
  3. Share: You can share the notebooks through the Git repository such as GitHub. If you add Open in Studio Lab button, the readers can copy the notebook or clone the repository by clicking button.

📓 Examples

Computer Vision

No Title Open in Studio Lab
1 Train an image classification model with PyTorch Open in SageMaker Studio Lab
2 Weather Classification for Disaster Risk Reduction with DenseNet-161 Open in SageMaker Studio Lab

Natural Language Processing

No Title Open in Studio Lab
1 Finetune T5 locally for machine translation on COVID-19 Health Service Announcements with Hugging Face Open in SageMaker Studio Lab

Geospatial Data Science

No Title Open in Studio Lab
1 Getting Started With Geospatial Data Analysis Open in SageMaker Studio Lab
2 Exploratory Analysis for NOAA Weather and Climate Dataset Open in SageMaker Studio Lab

Connect To AWS

No Title Open in Studio Lab
1 Using SageMaker Studio Lab with AWS Resources Open in SageMaker Studio Lab
2 Deploy A Hugging Face Pretrained Model to Amazon SageMaker Serverless Endpoint - Boto3 Open in SageMaker Studio Lab

Custom Environments

Thanks to the expandability of Jupyter Notebook, you can run not only Python but also another language Kernel such as R, Julia. Here is the example environment.yml files to set up the specific framework / language.

You can create the environment by copying the .yml file and right click copied .yml file in Studio Lab and select "Build Conda Environment".

Programming language environment

Speficic framework environment

Community contents

Here are some more examples from the community.

Studio Lab Examples in GitHub.

Please add amazon-sagemaker-lab tag to your repositories that use Studio Lab! We will pick up the popular repositories in here or our blog.

⚖️ License

This project is licensed under the Apache-2.0 License.

🤝 Contributing

Although we're extremely excited to receive contributions from the community, we're still working on the best mechanism to take in examples from external sources. Please bear with us in the short-term if pull requests take longer than expected or are closed.

Please read our contributing guidelines if you'd like to open an issue or submit a pull request.

🔎 References