A/B testing ML models in production: why, when, & how

A/B testing is a staple of software development and marketing, but it's often overlooked in the world of machine learning.Why bother A/B testing your ML models when you can just let them loose in the wild and see what happens?It turns out that there are several good reasons to A/B test your ML models before and while delivering them to production.Join Yuval Fernbach, Qwak’s co-founder and CTO to learn more about ML model deployment strategies:

  • How Shadow, Canary and AB deployment methodologies work for ML Models
  • Why A/B testing is important for ML
  • When you should A/B test, and how to go about setting up an effective test.

By the end of this session, you'll have an understanding of ML models deployment strategies and how to plan your model rollout effectively.

Yuval Fernbach

Yuval Fernbach

CTO & Co-founder

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At JLL our development is very time sensitive. As a result of implementing Qwak, we improved our execution time by 4.5X."

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Qwak has allowed us to work to the highest engineering standards from day one and to invest the majority of our efforts in our business challenges and not into plumbing."

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