🚀 Join us November 30 for the Evidently monthly demo and Q&A. Register now →
Give us a star ⭐️ on GitHub to support the project!

MLOps guides

Learn about ML model evaluation, monitoring and MLOps with our in-depth guides.

machine learning in production
OPEN-SOURCE ML OBSERVABILITY COURSE
ML monitoring

Open-source ML observability course

Want to learn production ML monitoring? Sign up for our Open-source ML observability course for data scientists and ML engineers. It's free!

evaluation METRICS in machine learning
Data drift detection

How to detect drift on large datasets? 5 methods compared

We ran an experiment to help build an intuition on how popular drift detection methods behave. In this guide, we share the key takeaways and the code to run the tests on your data.

ML MONITORING METRICS
ML monitoring metrics

Monitoring ML systems in production. Which metrics should you track?

"ML monitoring" can mean many things. Are you tracking service latency? Model accuracy? Data quality? This guide organizes everything one can look at in a single framework.

Data drift detection
Data drift detection

Which test is the best? We compared 5 methods to detect data drift on large datasets

We ran an experiment to help build an intuition on how popular drift detection methods behave. In this guide, we share the key takeaways and the code to run the tests on your data.

Shift happens: we compared 5 methods to detect drift in ML embeddings

Monitoring embedding drift is relevant for the production use of LLM and NLP models. We ran experiments to compare 5 drift detection methods. Here is what we found.

Drift detection in ML embeddings
The big book of ml monitoring
ML monitoring

The Big Book of ML Monitoring

A comprehensive introduction to ML monitoring, including a framework to organize ML monitoring metrics and steps to take when dealing with data drift in production.

By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.