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Welcome to Jupyter4NFDI

Jupyter4NFDI is an interactive, browser-based platform designed to provide seamless access to multiple cloud resources. Whether you are working on large-scale simulations, machine learning models, or data analytics, Jupyter4NFDI gives you the flexibility to perform these tasks interactively through familiar Jupyter Notebooks. While in the current phase only a one system is available, we will increase the number of resource providers in the future.

If you feel a feature is missing in Jupyter4NFDI, don't hesitate to reach out to us at jupyter4nfdi at lists.nfdi.de. We welcome your feedback to help expand the possibilities within Jupyter4NFDI.

Exploring JupyterHub options within NFDI

Jupyter4NFDI provides a central JupyterHub instance accessible to everyone within the NFDI. Additionally, various consortia and partners host their own JupyterHubs tailored to meet the specific needs of their users, resources, or environments. These dedicated JupyterHubs are often optimized for and restricted to particular user groups. You can explore the other available JupyterHubs here.

Why Use Jupyter4NFDI?

By using Jupyter4NFDI, you gain access to:

1. Cloud Power in Your Browser

Jupyter4NFDI connects you to cloud resources, offering scalable computing power for your workflows, including smaller data analysis tasks, web applications, and development environments.

2. Easy-to-Use Interface

The platform uses the popular Jupyter Notebook interface, making it easy for users of all skill levels to interact with powerful computational resources. You can run code, develop models, and perform analyses all from your web browser.

3. Interactive Development

Develop and test code interactively with instant feedback, enabling fast iteration of data science workflows, simulations, and machine learning models.

4. Use Custom Docker Images

Jupyter4NFDI supports custom Docker images, meaning you can define and use your own computing environment. This flexibility allows you to pre-install specific dependencies, configure your environment exactly as needed, and run reproducible computational workflows across multiple sessions.

5. GitHub-Based Environment with Binder

Through repo2docker integration, Jupyter4NFDI allows you to use the mybinder.org infrastructure to build Docker images directly from your GitHub repositories. This feature enables you to turn a GitHub repo into a fully functional environment without manually building Docker images, making your code and environment highly portable and shareable.

6. Access to Specialized Libraries and Tools

Jupyter4NFDI provides pre-configured environments with libraries optimized for cloud use cases, including scientific computing and machine learning tools such as TensorFlow, PyTorch, and more.

Use Cases

Jupyter4NFDI is ideal for:

  • Machine Learning: Train machine learning models at scale using cloud resources.
  • Data Science and Analytics: Analyze and visualize large datasets interactively, leveraging cloud resources depending on your requirements.
  • Scientific Research: From bioinformatics to materials science, accelerate your research using cloud resources.
  • Workshops and Training: Jupyter4NFDI is a great platform for hands-on workshops and training sessions. Instructors can create custom environments, share notebooks, and guide participants through interactive coding exercises on cloud infrastructure. This makes it ideal for educational and professional development settings.

Getting Started

To begin using Jupyter4NFDI, just follow these simple steps:

  1. Visit the website: Go to hub.nfdi-jupyter.de.
  2. Login: Authenticate via Helmholtz AAI. More information here.
  3. Select a system: Currently only JSC-Cloud available. More to come!
  4. Start and have fun: Launch your Jupyter environment and start working on your projects, whether they involve data science, machine learning, simulations, or training workshops.

Enjoy the power of cloud resources right from your browser!