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:
By the end of this session, you'll have an understanding of ML models deployment strategies and how to plan your model rollout effectively.
CTO & Co-founder
"From the get go, it was clear that Qwak understand our needs and requirements. The simplicity of the implementation was impressive.
Automatic deployment and continuous training were crucial to allow us to scale. Qwak gave us a type of "Jenkins" for machine learning."
"Using Qwak allowed us to focus on creating a business impact rather than spending valuable time on our infrastructure setup.
At JLL our development is very time sensitive. As a result of implementing Qwak, we improved our execution time by 4.5X."
"With Qwak we were able to improve our ML delivery dramatically.
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."