metric-learn provides Python implementations of metric learning algorithms.
Open source
24 alternativesHow do numpy-ML and metric-learn compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | numpy-ML | metric-learn |
|---|---|---|
| What it is | numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package. | This metric-learn repository contains Python implementations of metric learning algorithms. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Yes | Yes |
| Language | English | English |
| Alternatives |
Sites similar to both numpy-ML and metric-learn.
metric-learn provides Python implementations of metric learning algorithms.
hyperopt-sklearn uses hyperparameter optimization to select machine learning algorithms for scikit-learn.
Karate Club offers algorithms for unsupervised learning on graph data in Python.
BayesO provides a Python package for Bayesian optimization algorithms and related modeling tasks.
pomegranate provides flexible probabilistic modeling tools and algorithms for Python users.
Use Learnergy, a Python library for training and working with energy-based machine learning models.