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 ...

Notebooks are a key tool used by data scientists to experiment with AI models rapidly and share insights using interactive computation and code snippets.

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.

Currently there are no restrictions to the amount of data or the number of notebooks that can be created in the Electronic Research Notebook service. However, there is a limit on the maximum ...

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 ...

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 ...

Carbide is designed more like a Jupyter notebook, allowing for live markup, annotation, and manipulation of code and data An experimental new in-browser IDE is attempting to provide software ...

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.