Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
Appears on
Quick read
Latest capture 2026-10-08 03:07
Archive status reflects the last catalog sync, not a maintenance assessment. Check recent releases, issue responses, and fit for your project with the repository shortlisting checklist.
0 paths
Agent instructions and tool configuration found in this repository.
No config files detected.
9 observed captures since 2026-05-22. Observed captures are shown by default.
Stars from first capture 0
Observed captures only
All tracked data
Observed snapshots
Observed snapshots
Nearest indexed repositories by embedding similarity.
scikit-learn: machine learning in Python
An intuitive library to add plotting functionality to scikit-learn objects.
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
