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Vite Releases Technical Preview of Rolldown-Vite, a Rust-Based Bundler
Vite releases Rolldown-Vite, a Rust-based bundler preview offering faster builds and lower memory usage as a drop-in replacement for Vite.
|Build Status| |Azure Pipelines| |Coverage| |Doc Status| |Discourse| |Version Status| |NumFOCUS|
Dask-ML provides scalable machine learning in Python using Dask <https://dask.org/>
__ alongside popular machine learning libraries like Scikit-Learn <http://scikit-learn.org/>
, XGBoost <https://ml.dask.org/xgboost.html>
, and others.
You can try Dask-ML on a small cloud instance by clicking the following button:
.. image:: https://mybinder.org/badge.svg :target: https://mybinder.org/v2/gh/dask/dask-examples/main?filepath=machine-learning.ipynb
New BSD. See License File <https://github.com/dask/dask-ml/blob/main/LICENSE.txt>
__.
.. _documentation: https://dask.org .. |Build Status| image:: https://github.com/dask/dask-ml/workflows/CI/badge.svg?branch=main :target: https://github.com/dask/dask-ml/actions?query=workflow%3A%22CI%22 .. |Azure Pipelines| image:: https://dev.azure.com/dask-dev/dask/_apis/build/status/dask.dask-ml?branchName=main :target: https://dev.azure.com/dask-dev/dask/_build/latest?definitionId=1&branchName=main .. |Coverage| image:: https://codecov.io/gh/dask/dask-ml/branch/main/graph/badge.svg :target: https://codecov.io/gh/dask/dask-ml/branch/main :alt: Coverage status .. |Doc Status| image:: https://readthedocs.org/projects/ml/badge/?version=latest :target: https://ml.dask.org/ :alt: Documentation Status .. |Discourse| image:: https://img.shields.io/discourse/users?logo=discourse&server=https%3A%2F%2Fdask.discourse.group :alt: Discuss Dask-related things and ask for help :target: https://dask.discourse.group .. |Version Status| image:: https://img.shields.io/pypi/v/dask-ml.svg :target: https://pypi.python.org/pypi/dask-ml/ .. |NumFOCUS| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A :target: https://www.numfocus.org/
FAQs
A library for distributed and parallel machine learning
We found that dask-ml demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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