marimo

?? Announcing Marimo's $5M seed fundraise, led by Anthony Goldbloom and Shyam Mani at AIX ventures https://lnkd.in/gnAVCNmE We're honored to be backed by industry pioneers who are champions open-source: Jeff Dean (Google), Clem Delangue ?? (HuggingFace), Ben Hamner (ex-Kaggle, Sumble), Charlie Marsh (Astral), Paige Bailey (Google), Lukas Biewald (Weights and Biases), Wes McKinney (Posit, Composed Ventures), Jordan Tigani (MotherDuck), and Shane Barratt. With over 7.8k GitHub stars, 60+ contributors, and 1k members on Discord, our community is going strong. Today, marimo is used at companies and universities across the world, including Mozilla AI, BlackRock, Stanford, and even the MLB. Our fundraise lets us keep doing what we've already been doing -— building the world's best Python notebook, which will always be free, open-source, and permissively licensed. It also gives us the room to explore building other tools for working with data. If you like what we're doing, follow along or participate on GitHub and Discord, and stay tuned for a lot of exciting updates.

?? We've launched marimo on Product Hunt! https://lnkd.in/g9QEJFTJ marimo is the next-generation of Python notebooks. Run reproducible experiments, version with Git, deploy as an app, and execute as a script. All from AI-enabled editor. To show support, please upvote or leave a comment!

We're launching on Product Hunt soon, and we could use your help! Click through to the Product Hunt link to sign up for our launch ??

We've revamped our gallery of example marimo notebooks! Gallery link: https://marimo.io/gallery Our gallery showcases exemplary notebooks from our community, including an analysis of generative AI use cases by Anthony Goldbloom, a tutorial on activation functions for neural networks by Srihari Thyagarajan, a hands-on exploration of PCA by ?? Vincent Warmerdam, an interactive tutorial on hypothesis testing by Davide Eynard, marimo slides on STEM probes by Georgios Varnavides, a lesson on trajectory planning for spacecraft by Philipp Schiele, and a tutorial on signal decomposition by Bennet Meyers. When I started working on marimo, one of my primary goals was to make a tool that empowered others to explore and present data in new ways. That's why it's so gratifying and inspiring to see all the awesome things that our community is making. Thank you! ??

??? Analyze Formula 1 drivers with this marimo application running entirely on DuckDB wasm (i.e. entirely in your browser, no server) Feel free to fork the notebook and play around with it yourself! https://lnkd.in/eEuaPmuB

marimo is having its year end community call on November 15, 2024 from 10-11 AM PST. Join us as we discuss the latest ecosystem updates, community spotlights, roadmapping, and more!

Spaces on Hugging Face let you deploy marimo notebooks with just one click. Our community is already publishing cool things, like this notebook by Alonso Silva Allende that pulls back the curtains on LLM prompting: https://lnkd.in/gkzKGMzK

marimo is the only open-source Python notebook that can be seamlessly deployed as an interactive web app. We want to make it as easy as possible for our users to share their work on any platform. That's why we're excited to announce that, starting today, you can deploy marimo notebooks as apps with just one click on Hugging Face Spaces. Check out Caleb Fahlgren's video below for a demo!

In this blog, Anthony Goldbloom studies generative AI projects planned or underway at enterprises and discovers a previously overlooked trend: the most common use case of generative AI is data analytics, not customer support or marketing. Anthony's study was performed in a marimo notebook — marimo's built-in reactivity and interactivity lets you present and interact with data in ways that are just not possible in Jupyter notebooks. Check out the notebook at this link: https://lnkd.in/gkSCxurd

Read how Maria Mouschoutzi uses NetworkX and marimo to uncover hidden structures in Victor Hugo’s masterpiece Les Misérables, in her latest Towards Data Science blog: In the post, Maria walks through "building an interactive Marimo notebook for social network analysis, utilizing the NetworkX Python library and the?Les Misérables?social network dataset ... uncovering themes of justice, love, and sacrifice that define the novel’s narrative."