Concept drift is one of the main reasons why machine learning models fail post-deployment. However, unlike Covariate Drift or Data Quality, concept drift can almost always be fixed by retraining the model. Next Thursday, February 19th, Wojtek will introduce nannyML’s latest algorithm (the only) fully capable of detecting concept drift and estimating its magnitude. If you’re a Data Scientists with models in production, join us for a discussion about:

- The 2 reasons why machine learning models fail

- How to estimate concept drift magnitude

- How to automatically retrain your models with concept drift detection After the webinar, you’ll be fully equipped with the knowledge and tools to prevent your machine-learning models from failing silently.