Are data scientists moving away from Jupyter Notebooks?

In March this year, Aqua Security’s Team Nautilus discovered a Python-based ransomware that was using Jupyter Notebooks to access and target other environments.
Fernando Perez and Brian Granger spun off Project Jupyter from IPython in 2014. The name Jupyter was a reference to the three main programming languages that Jupyter supports, which are Julia, Python and R besides also being an homage to the notebooks that Galileo wrote on when he discovered Jupiter’s moons. Immediately after its release, a GitHub analysis showed that more than 2.5 million public Jupyter Notebooks were in use by September 2018. For data scientists, Jupyter became the staple environment and often the first tool they were introduced in a data science course. They were a great way to showcase a user’s work since both the code and the results can be seen right next to each other. They were also built for sharing insights easily with colleagues. But even as data scientists
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Picture of Poulomi Chatterjee
Poulomi Chatterjee
Poulomi is a Technology Journalist with Analytics India Magazine. Her fascination with tech and eagerness to dive into new areas led her to the dynamic world of AI and data analytics.
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