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?

Originally developed for data science applications written in Python, R, and Julia, Jupyter Notebook is useful in all kinds of ways for all kinds of projects: Data visualizations.

Data scientists are explorers. They use Jupyter Notebooks, one of the most popular environments for data science analysis, to begin work toward creative solutions to big problems. But once those ...

DataRobot Notebooks join a crowded field of data science notebooks, including the popular Jupyter Notebooks, as well as notebooks from Deepnote, Anaconda, Databricks, AWS, and many others.

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 ...

Jupyter Notebook is an open source web environment for data visualization. The modular software is used to model data in data science, computing, and machine learning.

What’s a Jupyter Notebook? Known primarily for its use in data science, Jupyter Notebook is an open-source web application similar to Google Docs, but more versatile. With Jupyter Notebook, students ...

The extension links Jupyter Notebook with Microsoft Excel seamlessly, unlocking a host of possibilities for what you can do with processing data inside Excel.

Apache Zeppelin joins a growing list of data science notebooks that include Databricks Cloiud, Jupyter (the successor to the iPython Notebook), R Markdown, Spark Notebook and others. Backends to ...

Jupyter Notebooks, even though tightly tied to data science darling programming language Python, can now be done with .NET languages C# or F#. The popular notebooks provide interactive environments -- ...