Also adds a new code interpreter to its conversational analytics agent in Looker to help business users perform more complex ...

feature Apr 22, 2019 7 mins Analytics Data Science Python Jupyter Notebook combines live code, graphics, visualizations, and text in shareable notebooks that run in a web browser Credit: NASA / JPL ...

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.

For data scientists, Python integration with Jupyter Notebooks now enables users to create and share documents that contain live code, equations, visualizations and explanatory text.

JupyterHub brings the power of notebooks to groups of users. It gives users access to computational environments and resources without burdening the users with installation and maintenance tasks.

"A hands-on session and guided tutorial for advanced users to explore how to use the EO4SD CR platform Jupyter Notebook, including how to access EO data, conduct analyses and extract data time series.

TOOLBOX 30 October 2018 Why Jupyter is data scientists’ computational notebook of choice An improved architecture and enthusiastic user base are driving uptake of the open-source web tool.

This includes development environments (such as Jupyter Notebook), tools (like data pipelines and MLOps platforms), open-source components (such as Hugging Face models) and runtime elements (such ...

The post details working with ML.NET with Jupyter Notebooks for machine learning projects and .NET for Apache Spark for Big Data with projects in .NET. "The initial set of features we released needed ...