Data science algorithms, in contrast to traditional software, are often nondeterministic. The correctness of an algorithm is much more subjective; therefore, being able to easily visualize intermediate stages in a data processing pipeline is tremendously important.
Pascal Bugnion demonstrates how to use Jupyter widgets to set GUIs up as part of the data science process. Join in to learn how to build human interaction into your data science process with as little friction as possible.
Pascal Bugnion is a data engineer at ASI Data Science, where he is working to build SherlockML, a collaborative platform for elite data scientists. Pascal is a maintainer of Jupyter widgets, a library for building user interfaces in Jupyter notebooks, and the author of Scala for Data Science. He holds a PhD in theoretical condensed matter physics from Cambridge University.
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