Loved by hundreds of thousands of data professionals
Amazon S3 Buckets in Jupyter notebooks
With Amazon S3 you can easily store any object in the cloud.
When connected to a Deepnote notebook, the bucket will be mounted along with the notebook's filesystem. Then you can easily reference, upload, delete or update any file that lives in the bucket. S3 can be used to store large datasets that will serve as inputs to training or analysis, or you can directly save there the outputs of your work.
Created for collaboration
Deepnote runs seamlessly in the cloud, making environment management and collaboration with your team a non-issue. And sharing work is as easy as sending a link or email invite.
Organize your work
Collaborate & comment
Sharing made simple
Integrates with your data stack
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.Browse integrations →