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@jupyter-naas

NaasAI

jupyter-naas
World

Sponsor the creators of the world's biggest catalog of data templates 🌎

Over the past 20 years, we have accumulated a ton of data. But what we miss is making this data really meaningful.
To do so we need to access it, understand it, and take action.
But not everyone is able to do this.

That’s why we created Naas, an all-in-one platform on top of Project Jupyter that enables anyone to build solutions (data products or services) using notebook templates.

With a community of +100 open source contributors, we are building the world's biggest catalog of data science templates: the awesome-notebooks, and provide a stable environment to run them in the cloud : Naas Cloud.

But running this project has costs.

We need to manage the collaborative work at scale to:

  • Produce templates people will love
  • Ensure the quality people deserved

So, whether you are an individual or organization, you can sponsor us here on Github.
By providing financial support to Naas, you will be able to push for prioritized template production on the Product Roadmap and get special benefits like extra computing power credits in the Naas cloud offering.

The first level of sponsoring is set at 5$/month, and if we want to cover our costs (servers for free plans and overheads), we need to be 5000 people, so every little bit helps.

Thanks in advance for your support.
💚 Spread the open source love.

Jeremy, Naas core team lead

5 sponsors have funded jupyter-naas’s work.

@jupyter-naas

With $25000/month, Naas's core team can focus on managing the community, offer a sustainable free tier on Naas Cloud, and give back to creators.

@VolcanoGunshot
@Dr0p42
@jravenel
Private Sponsor
@alexismonville

Meet the team

Featured work

  1. jupyter-naas/awesome-notebooks

    A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.

    Jupyter Notebook 2,707
  2. jupyter-naas/naas

    Low-code Python library to safely use notebooks in production: schedule workflows, generate assets, trigger webhooks, send notifications, build pipelines, manage secrets (Cloud-only)

    Python 286
  3. jupyter-naas/drivers

    Low-code Python library enabling access to APIs, tools, data sources in seconds.

    Python 57
  4. jupyter-naas/data-product-framework

    A framework to create powerful and flexible data products combining automation, analytics, and AI using Notebook templates.

    Jupyter Notebook 15

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