# evidentlyai/evidently

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7,137 stars · 793 forks · Jupyter Notebook · apache-2.0

## Links

- GitHub: https://github.com/evidentlyai/evidently
- Homepage: https://discord.gg/xZjKRaNp8b
- awesome-repositories: https://awesome-repositories.com/repository/evidentlyai-evidently.md

## Topics

`data-drift` `data-quality` `data-science` `data-validation` `generative-ai` `hacktoberfest` `html-report` `jupyter-notebook` `llm` `llmops` `machine-learning` `mlops` `model-monitoring` `pandas-dataframe`

## Tags

### Part of an Awesome List

- [Application Development](https://awesome-repositories.com/f/awesome-lists/ai/application-development.md) — Framework for monitoring and testing ML and LLM systems.
- [General Machine Learning](https://awesome-repositories.com/f/awesome-lists/ai/general-machine-learning.md) — Tool for analyzing ML models during validation and production.
- [LLM Observability and Evaluation](https://awesome-repositories.com/f/awesome-lists/ai/llm-observability-and-evaluation.md) — Framework for evaluating and monitoring ML and LLM systems.
- [Machine Learning Operations](https://awesome-repositories.com/f/awesome-lists/ai/machine-learning-operations.md) — Tool for analyzing and monitoring data and model drift.
- [Model Evaluation and Benchmarking](https://awesome-repositories.com/f/awesome-lists/ai/model-evaluation-and-benchmarking.md) — Framework for evaluating, testing, and monitoring ML and LLM systems.
- [Observability And Monitoring](https://awesome-repositories.com/f/awesome-lists/ai/observability-and-monitoring.md) — Analyzes machine learning models for drift and performance issues.
- [Data Validation](https://awesome-repositories.com/f/awesome-lists/data/data-validation.md) — Monitors and evaluates machine learning models in production.
- [Observability and Evaluation](https://awesome-repositories.com/f/awesome-lists/devtools/observability-and-evaluation.md) — Evaluation and monitoring framework for ML and LLM systems.