This metric-learn repository contains Python implementations of metric learning algorithms.
Open source
24 alternativesnumpy-ML
numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
About numpy-ML
numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
numpy-ML is an open-source project hosted on github.com, listed in our ML Training & Optimization collection. Because the code is public, you can read how it works, run your own copy or contribute improvements.
Not quite what you need? Close alternatives include metric-learn, metric-learn, and hyperopt — compare them below.
numpy-ML at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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numpy-ML FAQ
What is numpy-ML?
numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
What is numpy-ML used for?
People use numpy-ML for python, git, and machine learning, within our ml training & optimization category.
Is numpy-ML open source?
Yes. The source code is published at github.com/ddbourgin/numpy-ml.
Is numpy-ML working?
github.com responded when checked on Oct 6, 2026. Its current availability has not been confirmed.
What are the best alternatives to numpy-ML?
Popular alternatives to numpy-ML include metric-learn, metric-learn, hyperopt, and bayeso. We list 12+ options matched by topic, tags and features.
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