The Conference for Machine Learning Innovation

Keep an eye on AI — Monitor ML models in production

Session
Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until November 03:
✓ Save up to €494
✓ 10% Team Discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Register until November 03:
✓ Save up to €494
✓ 10% Team Discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now

We have built a training pipeline and deployed our first machine learning model into production. But our data science project is far from over. Even a production model faces many challenges. Unlike "traditional" software, the quality of a machine learning system deteriorates over time. A model that is deployed in production and not retrained will degrade. It will never work as well as it did on day one. Therefore, we need to monitor it and decide when to build and release a new version. 

You’ll leave this talk with an understanding of how we monitor machine learning models in production. We will talk about fast deployment cycles, DevOps, and deciding if our model still delivers business value. You’ll learn about failure modes of ML models and how we can detect them. Also, we will explore the use of A/B-testing for machine learning and little deployment strategies that can prevent big disasters when you retrain your model.

This Session belongs to the Diese Session gehört zum Programm vom MunichMunich program. Take me to the program of . Hier geht es zum Programm von Singapore Singapore .

This Session belongs to the Diese Session gehört zum Programm vom MunichMunich program. Take me to the program of . Hier geht es zum Programm von Berlin Berlin .

Take me to the full program of Zum vollständigen Programm von Munich Munich .

This Session Diese Session belongs to the gehört zum Programm von MunichMunich program. Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

Behind the Tracks