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Evidently AI

Open-source ML monitoring — detect data drift and model degradation

MLOps Apache 2.0 Library Intermediate

Stats

GitHub stars★ 6k+
LicenseApache 2.0
HostingLibrary
DifficultyIntermediate

Get started

Official docs and GitHub repo

Visit Evidently AI ↗ View on GitHub ↗

What is Evidently AI?

Evidently is an open-source library for monitoring ML models in production. Generate visual reports on data quality, data drift, model performance, and target drift. Essential for any production ML system — models degrade silently without monitoring.

Quick start

1
pip install evidently
2
from evidently.report import Report
3
from evidently.metric_preset import DataDriftPreset
4

report = Report(metrics=[DataDriftPreset()])

5

report.run(reference_data=ref, current_data=curr)

6

report.save_html("report.html")

Use cases

Data drift detection

Model performance monitoring

Data quality reports

Production ML health checks

Compatible models

Framework agnostic — monitors any model's input/output data

Why this matters for India

// india context

Non-negotiable for production ML. A model deployed without monitoring is a liability.