#scikitlearn
Live, measured metrics for the hashtag #scikitlearn from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #scikitlearn
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-09-26 17:12 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-09-26 17:12 UTCNo related tags with measured usage found for #scikitlearn.
Live pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-09-26 17:12 UTCEverything below is measured over the latest 40 public posts (spanning ~14656 hours).
Posting hours (UTC) — busiest: 15:00
Languages: English (20) · Russian (16) · Italian (1) · Portuguese (1) · French (1)
Avg boosts / post: 2.7
Top of the latest posts
scikit-learn 1.9.1 We're happy to announce the 1.9.1 release. https://whatsnew.fyi/product/scikit-learn/releases/1.9.1 #ScikitLearn #AI
Как проверить ML‑модель перед продом и избежать утечки данных в scikit‑learn Высокая метрика на кросс‑валидации ещё не означает, что модель покажет такой же результат после запуска. Разрыв между офлайном и продакшеном часто появляется из‑за
Ипотечный кризис 2008 через свой риск-движок: в деньгах слом виден на год раньше, чем в ROC-AUC Модель кредитного риска, обученная на данных до 2009 года, ранжирует займы с ROC-AUC 0.89. Ожидаемые потери портфеля она оценила в 161 млн долла
What “scikitlearn” means
Wikipediascikit-learn is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Scikit-learn is a NumFOCUS fiscally sponsored project.
“Scikit-learn” on Wikipedia (CC BY-SA) →#scikitlearn across platforms
every network with a public tag surfaceFollow #scikitlearn straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/scikitlearn