Deepnote – a Collaborative Data Science Notebook
Deepnote – a Collaborative Data Science Notebook


Deepnote is a new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud.
Long abstract version: Deepnote is a collaborative data science notebook. It's built on and fully compatible with the Jupyter ecosystem, but to address the key pain points of notebooks, we've introduced some significant changes. First, Deepnote is collaborative - it allows for real-time interactions, comments and is easily shareable (just like Google Docs). It is intuitive enough for non-technical users, yet powerful and flexible for data scientists. Second, the interface encourages best practices - writing clean code, defining dependencies, and building reproducible notebooks. Third, Deepnote seamlessly integrates with the rest of your data stack - other services, databases, ML platforms, and the Jupyter ecosystem. In this session, we will showcase what we're building at Deepnote and share plans for future iterations.


Jakub Jurovych is a founder and CEO of Deepnote. As an engineer, Jakub built tools for JavaScript development and worked on Firefox DevTools. Jakub studied Computer Science at Cambridge University, focusing on Human-Computer Interaction, Machine Learning and Computer Vision. Jakub is a YC alumnus (2019) and ranked in Forbes 30 Under 30. In 2019, Jakub founded Deepnote, a new kind of data science notebook.

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