Contribute Media
A thank you to everyone who makes this possible: Read More

Detecting drift: how to evaluate and explore data drift in machine learning systems

Description

Speaker:: Emeli Dral

Track: PyData: Machine Learning & Stats When your ML model is in production, you might observe input data and prediction drift. In absence of ground truth, drift can serve as a proxy for the model performance. But how exactly to evaluate it? In this talk, I will give an overview of the possible approaches, and how to implement and visualize the results.

Recorded at the PyConDE & PyData Berlin 2022 conference, April 11-13 2022. https://2022.pycon.de More details at the conference page: https://2022.pycon.de/program/ASW8CJ Twitter: https://twitter.com/pydataberlin Twitter: https://twitter.com/pyconde

Details

Improve this page