This metric-learn repository contains Python implementations of metric learning algorithms.
Open source
24 alternativeshyperopt
vsnumpy-ML
hyperopt vs numpy-ML
How do hyperopt and numpy-ML compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | hyperopt | numpy-ML |
|---|---|---|
| What it is | hyperopt-sklearn uses hyperparameter optimization to select machine learning algorithms for scikit-learn. | numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Not stated | Yes |
| Language | English | English |
| Alternatives |
Other options to consider
Sites similar to both hyperopt and numpy-ML.
metric-learn provides Python implementations of metric learning algorithms.
Open source
24 alternatives
BayesO provides a Python package for Bayesian optimization algorithms and related modeling tasks.
Open source
24 alternatives
Determined manages distributed model training, hyperparameter tuning, experiment tracking, and resources.
Open source
24 alternatives
Karate Club offers algorithms for unsupervised learning on graph data in Python.
Open source
24 alternatives
ML-Ensemble provides Python tools for high-performance ensemble learning with scikit-learn.
Open source
24 alternatives