In this talk, we’ll showcase, through ML monitoring and notebooks, how data scientists and ML engineers can leverage ML monitoring to find the best data and retraining strategy mix to resolve machine learning performance issues. This data-driven, production-first approach enables more thoughtful retraining selections, shorter and leaner retraining cycles, and can be integrated into MLOps CI/CD pipelines for continuous model retraining upon anomaly detection.

November 1st - 3rd, 2022 | San Francisco

Data-driven retraining with production insights

In this webinar, we’ll learn how to implement the 1st level of MLOps maturity and perform continuous training of the model by automating the ML pipeline. We’ll start with the ML pipeline and see how we can detect performance degradation and data drift in order to trigger the pipeline and create a new model based on fresh data.

August 16th, 2022 | 1:00 PM ET

Continuous MLOps pipelines: A dive into continuous training automation
Datalift summit cover

Swing by the Superwise booth and let’s talk MLOps and ML monitoring.

June 22nd - 24th, 2022 | Berlin

#Datalift summit
Chanllenges unique to fintech summit

to the Fintech industry. In this keynote, our head of product, will walk you through the challenges of unbalanced use cases, adversarial attacks, and delayed feedback for Fintech companies and share our best practices on how to overcome them.

Jun 22nd - 24th, 2022 | Berlin

The uncommon monitoring challenges unique to Fintech