IntelPython / scikit-learn_bench
scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms.
Why this job: matched by what the repo talks about: benchmark, bench, learn, framework
What it does
How to create a usable Python environment with the following required frameworks:
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 21 days ago
- Stars
- 124
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 83% closed
- 4 still open
- Pull requests
- 151 merged
- 17 waiting
- Releases
- None
- Never published
- No contributing guide
- Security policy (opens in new tab)
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
Topics
- benchmarks
- daal4py
- hacktoberfest
- machine-learning
- machine-learning-benchmarks
- scikit-learn-benchmarks
Project record
- JobEvals and observability
- StatusListed
- Commits284
- Forks76
- Watching10
- Stars in 28 days0
- CreatedOct 2, 2018
- First seen by usNov 7, 2026
- CheckedNov 8, 2026