Notebooks are typically used by data scientists for quick exploration tasks. In that regard they offer a number of advantages over any local scripts or tools. When properly set up by the organization, ...

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 ...

“With DataRobot Notebooks, data science teams can leverage a fully-managed, secure, and cloud-first solution that helps make their work a true team sport,” he said.

Data visualizations. Most people have their first exposure to Jupyter Notebook by way of a data visualization, a shared notebook that includes a rendering of some data set as a graphic.

Data management and documentation is an important part of the responsible conduct of research. Data that you create, record, compile or collect during your research is a valuable asset that needs to ...

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 ...

The problem with notebooks is that they're much better for experimental data science work than they are for production data engineering work. That's my own opinion, of course. But I stand by it.

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, the interactive data notebook for visualization and analysis with languages like Python and R, is undergoing a quiet but major reworking into a new product, JupyterLab. Jupyter’s ...

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.