Repository profile
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
Repository updates
Get generated benhamner/Metrics development summaries by email, or follow the weekly and monthly RSS feeds.
Sign in to subscribe by email. RSS feeds are public.
Sign in to subscribeTracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-07-07 03:14
6 captures since 2026-05-22
Stars from baseline 0
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-07-07 03:14
Python/requirements.txt
python ecosystem,
0 dependencies
Python/setup.py
python ecosystem,
0 dependencies
C#/Metrics/Metrics.csproj
dotnet ecosystem,
0 dependencies
C#/MetricsApp/MetricsApp.csproj
dotnet ecosystem,
0 dependencies
C#/Metrics/Metrics.sln
dotnet ecosystem,
0 dependencies
C#/Metrics/MetricsTests/MetricsTests.csproj
dotnet ecosystem,
0 dependencies
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
A library of metrics for evaluating recommender systems
Metric learning algorithms in Python
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
Machine learning metrics for distributed, scalable PyTorch applications.
No description.
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
403 Forbidden | https://api.github.com/repos/benhamner/Metrics/readme | message=API rate limit exceeded for user ID 260990068. If you reach out to GitHub Support for help, please include the request ID CD4E:2C24A7:193946ED:17DA2A8D:6A4C6F1A and timestamp 2026-07-07 03:14:34 UTC. For more on scraping GitHub and how it may affect your rights, please review our Terms of Service (h | rate_limit_remaining=0 | rate_limit_reset=1783396811
