Sarah Diot-Girard
Sarah Diot-Girard has been working with Machine Learning since 2012 and she enjoys using data science tools to find solutions to practical problems. She is particularly interested in practical issues, both ethical and technical, coming from applying ML into real life. She gave talks about data privacy and algorithmic fairness, and software engineering best practices applied to data science.
Sessions
Engulfed in a tedious refactoring of your code, you’re adding the 7th layer of mocks to a test when you realise something must have gone wrong somewhere, but what ? You’ve written readable code, split into functions and classes to avoid long chunks of code, and yet, every time, you end up with hardly testable code, a test suite that runs for hours, functions with seventeen arguments, and you wonder if it’s you mocking the code or the code mocking you.
Follow the white rabbit with me to learn about usual problems of code organization and I/O architecture, and some tricks on how to handle I/Os and dependencies isolation. We might encounter a bit of SOLID advice, and maybe even a nice hat!