In David Taieb's view, the best line of code is the one you didn't have to write. Hence the inspiration behind PixieDust, an open source helper library, built by Taieb and his team. PixieDust makes it easier for users of Jupyter Notebooks to start analyzing data quicker, without nearly as much coding, and simplifies data science for developers and business users.
David shares the origin story behind PixieDust and how he built it (5:20), PixieDust's compatibility with the user's preferred flavor of Jupyter, be it Apache Spark, Python or Scala (7:54), some of the other rendering engines (Mapbox, Bokeh, Matplotlib) that come built in (13:08), the companion project of HTML- and CSS-powered PixieApps (15:13), and PixieDust's role in enabling businesses in the Middle East to make better data-driven decisions (18:58).
Register for the IBM Data Science Bootcamp at Spark Summit to learn the ins and outs of the open source PixieDust library and how it simplifies working in a Jupyter Notebook.
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