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 ...

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.

Tweet this In addition to the Jupyter Notebook integration, CoderPad has also upgraded its processing power to cater to projects that involve extensive data sets.

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 -- ...

Anaconda today announced support for Snowflake Notebooks, an interactive, cell-based data science notebook similar to Jupyter. The move will let data scientists, data analysts, and data engineers ...

Datalore combines the power of the Jupyter data science notebook with PyCharm, JetBrain’s integrated development environment (IDE) for Python. This gives users smart coding features from the PyCharm ...

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 ...

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 ...

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.