Romain Menegaux and Chakri Cherukuri demonstrate how to develop advanced applications and dashboards using open source projects, illustrated with examples in machine learning, finance, and neuroscience. Romain and Chakri first offer an overview of Jupyter’s widget ecosystem and components, including ipywidgets, bqplot, and pythreejs. They then explain how to link these widgets together using callback functions before sharing a few examples of advanced applications and dashboards developed using open source projects.
This session is sponsored by Bloomberg.
Romain Menegaux is a researcher on the Quantitative Financial Research team at Bloomberg LP, where he develops derivatives pricing models and applies machine learning to a variety of financial problems. Romain is one of the main developers of bqplot and an occasional contributor to ipywidgets.
Chakri Cherukuri is a researcher in the Quantitative Financial Research group at Bloomberg LP. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. Chakri is one of the main contributors to bqplot, a Jupyter Notebook–based interactive plotting library. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology, Chennai, and an MS in computational finance from Carnegie Mellon University.
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