d_rc
Joined 12 years ago
Joined 12 years ago
In general the main selling points are live collaboration (you can work on a notebook with you team as you'd do on a google doc), and integrations (you can plug-in your snowflake db, or s3 bucket or whatever, and have it connected for any further analysis, or a long-term training, etc.
For many non-software-developer data scientists, it's also easier to work in a cloud environment compared to installing stuff locally, and to version their notebooks in Deepnote instead of git. But this really depends on the particular workflow that one has.
Here's a public notebook in Deepnote if anyone wants to play around with the code or duplicate it: https://deepnote.com/project/Converting-Markdown-to-Epub-or-...
2 fun facts about Deepnote:
1. You can create a Custom environment by writing a Dockerfile with all the libraries you need to install and everytime you're in a need to re-use a similar functionality (e.g. convert yet another book to mobi), you can just fire it up and all will be preinstalled. https://docs.deepnote.com/environment/custom-environments
2. You can turn any notebook to a blogpost right away and publish within Deepnote directly.
Disclaimer: I'm a software engineer at Deepnote.