No credit card required. Run your first notebook in 30 seconds.
We built collaboration into Deepnote by default because data teams don’t work alone.
Deepnote runs seamlessly in the cloud, making environment management a non-issue. And sharing work is as easy as sending a link (think Google Docs).
“Deepnote allowed us get on the same page through collaboration, and everyone gets to use their preferred tools.”
Explore what data teams are building in Deepnote
Deepnote works with the tools and frameworks you’re already using and familiar with. Use Python, SQL, R, TensorFlow, PyTorch, and any of your favorite languages or frameworks. Easily connect to data sources with dozens of native integrations.
”Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds.”
Datastores and Metrics
We created Deepnote to make you more productive. Whether you work in a team or by yourself, Deepnote helps you clean your data, write complex queries, build predictive models, and ship beautiful apps.
Work with Python, SQL or R — all at the same time.
Visualize DataFrames as no-code configurable charts.
Go back in project history and restore past versions.
Get real-time hints when working in Python or SQL.
Collaborate with your team in real time.
Run your notebooks hourly, daily, weekly, or monthly.
Run scripts, installations, and other tasks inside an integrated terminal.
Choose the right machine for the job and monitor performance.
Ensure everyone runs in the same shared environment.
Control who can view, comment, code, edit, and manage notebooks.
Collect feedback and iterate faster by working asynchronously.
Connect to your data warehouse and tools in seconds.
Secure by default by following the industry best practices like fine-grained access controls, SSO support or on-premise deployments.
Showcase your projects, jump in on the conversation, and learn faster by joining our community.
Got early access to @DeepnoteHQ.This stuff is insane! Super intuitive and amazing UX. It's like a collaborative VSCode + Jupyter + Colab.
Deepnote enables us to bring people into the phase of data science that’s all about experimentation, helps them understand our processes, and encourages folks to leverage data science in even more ways.
Awesome service for working on Jupyter Notebooks collaboratively. My students are currently using it for their machine learning class projects; and it's also useful for me to check & comment. Really cool is the data management. No mounting required, it's just drag and drop.
Our community forums are the best place to get started and get answers to your Deepnote and data science questions.Join community ->
Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently.
Machine learning is a very empirical discipline so iteration speed is everything - working in Deepnote is like code-review and rapid prototyping at the same time, saving valuable time in the iteration cycles.
No credit card required. Run your first notebook in seconds.