Data science notebooks are an important tool used by data science professionals for experimentation and collaboration. These interactive notebooks allow users to write and execute code for exploratory ...

Jupyter notebooks break out of their "show and tell" role into something more suitable to data engineers. Can JupyterLab turn notebooks into an Enterprise tool?

Traditionally, notebooks have been used to document research and make results reproducible, simply by rerunning the notebook on source data. But why would one want to choose to use a notebook instead ...

Deepnote, a startup that is building a data science platform on top of Jupyter-compatible notebooks, today announced that it has raised a $20 million Series A round co-led by Index Ventures and ...

Deepnote, a collaborative data science notebook for teams, raises $20 million in Series A funding from Index Ventures, Accel, Y Combinator, and Credo.

AI provider DataRobot is releasing DataRobot Notebooks, a fully integrated notebooks solution within the DataRobot AI platform that enables data scientists to collaborate across code-first workflows ...

Data teams everywhere can now use Deepnote 1.0 to make data science and analytics work more collaborative. In minutes, data teams can spin up a Deepnote Workspace, run analysis by connecting to ...

The new agent upgrades the Databricks Assistant, enabling it to help data practitioners complete repetitive tasks and ...

Many solutions for Data Science Notebooks, machine learning toolkits, machine learning platforms, and analytic suites are available as open source offerings.