Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK

Human-in-the-loop data science with Jupyter widgets

Pascal Bugnion (ASI Data Science)
16:3517:15 Thursday, 24 May 2018

Who is this presentation for?

  • Data scientists and data engineers

Prerequisite knowledge

  • A basic understanding of Python

What you'll learn

  • Learn how to build user interfaces in Jupyter notebooks


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.

Jupyter widgets allow for the creation of lightweight, interactive graphical interfaces directly in Jupyter notebooks. This provides the following advantages: graphical interfaces lead to a much shorter feedback loop for the data scientist, allowing them to rapidly experiment with their model; data scientists can use Python (rather than, say, JavaScript) to create user interfaces; the GUI is part of the pipeline, rather than a window onto it; and any output generated by the UI can be used for the next step of the pipeline.

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

ASI Data Science

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.