Nick Langellier
I am a senior machine learning engineer at VideaHealth, Inc. where I am currently developing AI models for automatic detection of dental diseases. My background is in astrophysics and I have 4 years experience as a teaching assistant at the University of Illinois at Urbana-Champaign and Harvard University. The coursework ranged from introductory to mid-level physics in both theoretical and laboratory settings. I have contributed to several conferences, most notably an invited talk at an exoplanet conference in Göttingen, Germany. There I presented my Ph. D work on improving exoplanet analysis pipelines through the use of machine learning.
Sessions
This tutorial is an introduction to Pydantic, a library for data validation and settings management using Python type annotations. Using a semi-realistic ML and / or scientific software pipeline scenario we demonstrate how Pydantic can be used to support type validations for scientific data structures, APIs and configuration systems. We show how the use of Pydantic in scientific and ML software leads to a more pleasant user experience as well as more robust and easier to maintain code. A minimum knowledge of Python type annotations, class definitions and data structures will be helpful
for beginners but not required.