scikit-learn
by scikit-learnscikit-learn: machine learning in Python
Statistical Machine Intelligence & Learning Engine
This is the project's own description from GitHub — we show it as-is rather than inventing details.
This project is listed under Statistics in Data & Analytics, a category made for analysts, businesses, researchers and data-curious users.
Do I need coding knowledge? Coding Knowledge Recommended. (Estimate based on project type: A developer tool/library — setup usually follows the README with basic coding skills. Always confirm from the repo's README.)
The source code is released under the NOASSERTION license. Open-source licenses like this usually allow free use, including commercial use — but always read the actual license file in the repository before relying on it. Note: the code being free does not mean hosted services, APIs or infrastructure around it are free.
Activity level: Very active · Last code update: 01 Nov 2026 · Created: 20 Nov 2014 · Open issues: 2
Official links: Official Website ↗ · Releases ↗ · Documentation (README) ↗
We never publish installation steps we have not verified — the README above is the source of truth.
⭐ 6428 stars · 🍴 1149 forks · 🐛 2 open issues · 💻 Language: Java · 📄 License: NOASSERTION · Default branch: master
scikit-learn: machine learning in Python
Umami is a privacy-first web and product analytics platform. Traffic, campaigns, behavior, conversions, and revenue in one place. No cookies, no surveillance, self-hosted or in…
Open source, privacy-first web analytics. Lightweight, cookie-free Google Analytics alternative. Self-hosted or cloud.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All…
Go language library for reading and writing Microsoft Excel™ (XLAM / XLSM / XLSX / XLTM / XLTX) spreadsheets
Count your code, quickly.