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On Demand

A/B Testing ML Models In Production: Why, When, & How

ML models deployment strategies and planning effective your model rollout
Yuval Fernbach
Yuval Fernbach
Co-founder & CTO at Qwak
at
at
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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.

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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.

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