How to Test your Machine Learning models - Goku Mohandas

What is testing ML and how it's different from testing deterministic code
Why it's important to test ML artifacts (data + models)
What testing data and testing models looks like (and I'll provide quick code snippets so people can see what it looks like)
Concluding thoughts on how testing relates to monitoring and continual learning.

Invited Talk by ‪@Goku-Mohandas‬ from https://madewithml.com

This talk was part of the workshop "Real-world Perspectives to Avoid the Worst Mistakes using Machine Learning in Science" at Pydata Global 2022, organised by Jesper Dramsch, Gemma Turon, and Valerio Maggio.

The workshop has received funding from the Software Sustainability Institute through the 2022 fellowship programme received by Jesper Dramsch.
https://dramsch.net/ssi

Find the programme of the workshop, transcripts and more resources here:
https://realworld-ml.xyz/

#MachineLearning #PydataGlobal