Dask-ML provides scalable machine learning in Python using Dask alongside popular machine learning libraries like Scikit-Learn, XGBoost, and others.
You can try Dask-ML on a small cloud instance by clicking the following button:
LICENSE
New BSD. See License File.
2 maintainers
Metadata
2 maintainers
Release files for dask-ml 2022.5.27
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dask-ml-2022.5.27.tar.gz | 597.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dask_ml-2022.5.27-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 746.2 kB
Release files / dask-ml-2022.5.27.tar.gz
| Download URL | dask-ml-2022.5.27.tar.gz |
|---|---|
| Size | 597.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.10.4
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Release files / dask_ml-2022.5.27-py3-none-any.whl
| Download URL | dask_ml-2022.5.27-py3-none-any.whl |
|---|---|
| Size | 148.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.10.4
|
