Scalable Machine Learning with Dask
active 2023-08-15 → 2026-05-27 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1017 days from 2023-08-15 to 2026-05-27. Pushes: 24 total, peak 8 in a day. Pull requests: 29 total, peak 7 in a day. Issues: 39 total, peak 4 in a day. Comments: 137 total, peak 20 in a day. Stars: 90 total, peak 2 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| TomAugspurger | 96 | 12 | 17 | 52 |
| phofl | 34 | 0 | 0 | 17 |
| milesgranger | 22 | 0 | 0 | 12 |
| pr38 | 15 | 0 | 1 | 10 |
| stsievert | 14 | 0 | 0 | 8 |
| github-actions[bot] | 11 | 11 | 0 | 0 |
| jrbourbeau | 10 | 1 | 2 | 4 |
| npk7 | 7 | 0 | 1 | 3 |
| wietzesuijker | 6 | 0 | 1 | 4 |
| fujiisoup | 5 | 0 | 2 | 3 |
| flying-sheep | 4 | 0 | 0 | 2 |
| stefanodesaraca | 3 | 0 | 0 | 1 |
| jacobtomlinson | 3 | 0 | 1 | 0 |
| Zethson | 3 | 0 | 0 | 1 |
| ivirshup | 3 | 0 | 0 | 1 |
| aazuspan | 3 | 0 | 0 | 1 |
| py-rh | 3 | 0 | 0 | 1 |
| narnia24 | 3 | 0 | 0 | 3 |
| GaetanLepage | 2 | 0 | 1 | 0 |
| indrajitsg | 2 | 0 | 0 | 1 |
Recent activity
Latest issues, pull requests and releases
- Issue comment#635chauhankaranraj2026-05-27 03:48WIP: Add stratified split feature to model_selection.train_test_split
- Issue comment#964TomAugspurger2026-01-04 13:47sklearn handles text labels differently than ml_dask on OneHotEncoding
- Issue#964TomAugspurger2026-01-04 13:47sklearn handles text labels differently than ml_dask on OneHotEncoding
- Issue comment#964ruthvik06122025-12-14 00:31sklearn handles text labels differently than ml_dask on OneHotEncoding
- Issue comment#1014pr382025-12-03 01:40add TF-IDF Transformer
- Issue comment#1021XinEDprob2025-09-30 16:58Support for Catboost models
- Issue comment#918TomAugspurger2025-09-27 16:54Update KMeans class information
- Issue comment#1021TomAugspurger2025-09-27 12:46Support for Catboost models
- Pull request#1020sergeyklay2025-08-18 16:04
- Issue#1019avalanche-pwn2025-05-19 14:04ColumnTransformer _hstack incompatible with scikit's version
- Issue comment#1018TomAugspurger2025-05-10 15:15CI Fixes
- Pull request#1018TomAugspurger2025-05-10 15:14
- Pull request#1018TomAugspurger2025-05-10 14:59
- Issue comment#1012TomAugspurger2025-05-10 14:34Tests failing with `ValueError: cannot broadcast shape (nan,) to shape (nan,)`
- Issue comment#1016TomAugspurger2025-05-10 14:33RuntimeError: Attempting to use an asynchronous Client in a synchronous context of `dask.compute`
- Issue comment#1012TomAugspurger2025-05-10 13:23Tests failing with `ValueError: cannot broadcast shape (nan,) to shape (nan,)`
- Issue#1012TomAugspurger2025-05-10 13:23Tests failing with `ValueError: cannot broadcast shape (nan,) to shape (nan,)`
- Issue#1012TomAugspurger2025-05-10 13:23Tests failing with `ValueError: cannot broadcast shape (nan,) to shape (nan,)`
- Pull request#1013TomAugspurger2025-05-10 13:23
- Issue comment#1013TomAugspurger2025-05-10 13:23fix: prevent broadcasting errors in r2_score using da.where()
- Issue comment#1014pr382025-05-07 19:19add TF-IDF Transformer
- Issue comment#1013TomAugspurger2025-05-07 00:22fix: prevent broadcasting errors in r2_score using da.where()
- Issue comment#1013wietzesuijker2025-05-06 21:56fix: prevent broadcasting errors in r2_score using da.where()
- Pull request#848gforsyth2025-05-02 20:50
- Issue#1017stefanodesaraca2025-04-06 17:52"joblib.externals.loky.process_executor.ShutdownExecutorError: cannot schedule new futures after shutdown" Error raised after i set some parameters to BaggingRegressor
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 90 stars here means stars gained during the window, not the repo's star count.