#xgboost
Live, measured metrics for the hashtag #xgboost from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #xgboost
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 06:06 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 06:06 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 06:06 UTCEverything below is measured over the latest 40 public posts (spanning ~20424 hours).
Posting hours (UTC) — busiest: 10:00
Languages: Russian (19) · English (19) · German (1) · Japanese (1)
Avg boosts / post: 0.3
Top of the latest posts
tidymodels has long supported parallelizing model fits across CPU cores. A couple of the modeling engines that #rstats #tidymodels supports for gradient boosting—#XGBoost and #LightGBM—have their own tools to parallelize model fits. A new b
there are precompiled xgboost #RStats binary packages with support for gpu acceleration with Cuda, so I made a nix-shell that installs it if you want to test it with the #Nix package manager https://github.com/b-rodrigues/xgboost-gpu-nix #R
#XGBOOST is fun
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/xgboost