Testing a Data Science Model
I have heard from other senior testers around the world that they know of data science teams but no testers testing the models, how do we have enough confidence what is produced is good enough? A model is a statistical black box, how to test it so we understand its behaviours to test is properly. Main aim would be to help inspire testers to explore data science models.
I’d like to share how I explored the world of data science when testing a model and how we can apply that if we find ourselves in this situation. It is an emerging area for testers and exciting.
I’d like to invite you to my talk where, we will go through my journey of discovering data science model testing and find the following takeaways useful not just for testing a data science model but day to day testing too.
1. Have a better understanding of what data science is.
2. Know how we can test models.
3. Know what existing skills we already have that we can apply in a data science team.
4. Leave with resources to help our teams’ better structure itself to have confidence in the data produced.
5. We'll look at what did or didn't work