Cut out the cloud share interactive Jupyter dashboards on a USB stick

A lot of data science visualizations are really throwaway web apps that aren’t intended to be public, or even cloud-based for private users. It’s not worth the infrastructure (and security risk) of locking down a hosting service to serve these given their short shelf-life. In fact, the web technologies employed are really only ‘borrowed’ from different scenarios where cloud or internet is important. It is only by accident that our visualizations were built with web-style technologies in the first place… so can we shift our thinking to take our head out of the clouds completely?

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Jupyter is the new Excel (but not for your boss)

Recently you may have seen the very insightful article called Jupyter is the new Excel, written by Semi Koen. She describes how many professionals immediately reach for Excel when faced with data-heavy analysis tasks, but she argues that for many ‘big data’ challenges it would make sense to work within a Jupyter Notebook instead.

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Introducing Jupyter Innotater

In a data science or machine learning project, you may prepare and study images or other data within a Jupyter notebook then need to annotate the data to augment the training or fix errors in your source data.

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