numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
Open source
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BayesO provides a Python package for Bayesian optimization algorithms and related modeling tasks.
About bayeso
BayesO is an open-source Python package for Bayesian optimization, a method for tuning and searching over functions that are expensive to evaluate. It is distributed as a repository on GitHub, with its online documentation hosted at bayeso.org. The package can be installed from PyPI with pip, from a local copy of the source code, or in editable development mode. Optional extras add the dependencies for development work and for running the examples.
The project provides a list of examples and a test suite in its repository. The maintainers state that the package is tested on Python 3.8 through 3.12. The code is released under the MIT License, and the project offers a citation entry for a 2023 paper in the Journal of Open Source Software.
Key features
- Python package implementing Bayesian optimization algorithms
- Installable from the PyPI repository with a single pip command
- Source-code installation for developers and editable development mode
- Optional extras for development and example dependencies
- Examples and tests included in the repository
- Released under the MIT License
Best for: Python developers and researchers who want to apply Bayesian optimization, such as for hyperparameter tuning in machine learning work.
Good for
- Open source under the MIT License
- Can be installed with pip from the PyPI repository
- Includes a citation entry and a published software paper
Watch out for
- The maintainers state testing only for Python 3.8 through 3.12
bayeso at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Good for
- Developers
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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bayeso FAQ
Which Python versions does BayesO support?
The maintainers state that the package is tested on Python 3.8, 3.9, 3.10, 3.11, and 3.12.
How do I install BayesO?
For user installation, run pip install bayeso. For a developer installation, run pip install . from the source root, or pip install -e . for editable mode.
Where is the documentation?
The online documentation is listed at bayeso.org.
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