evaluation METRICS in machine learning

A complete guide to classification metrics in machine learning

How to evaluate the quality of a classification model? In this guide, we break down different machine learning metrics for binary and multi-class problems.

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Confusion Matrix

How to create a confusion matrix for binary and multi-class models.

Accuracy, Precision, Recall

The difference between metrics and how to choose the appropriate one.

Multi-class Precision and Recall

How to calculate multi-class metrics by class, micro- and macro-averaging.

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.

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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.

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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.

See the guide ⟶

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.

See the guide ⟶

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.

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The big book of 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.

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MLOps guides

A complete guide to classification metrics in machine learning

Confusion Matrix

Accuracy, Precision, Recall

Multi-class Precision and Recall

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

How to detect drift on large datasets? 5 methods compared

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

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

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

The Big Book of ML Monitoring

ML in production newsletter