| Name | Version | Summary | date |
| e3md |
0.2.0 |
Library for machine learning on physical tensors |
2025-07-20 21:42:22 |
| tensorial |
0.4.4 |
Library for machine learning on physical tensors |
2025-07-20 20:26:28 |
| PyOghma-ML |
0.2.0 |
A Python Pipeline for Machine Learning with Oghma |
2025-07-19 16:19:02 |
| beast-backbones |
1.1.0 |
Behavioral analysis via self-supervised pretraining of transformers |
2025-07-17 21:44:57 |
| nunnpyy |
1.0.0 |
A collection of machine learning algorithms implementations |
2025-07-17 16:01:23 |
| mseep-zenml |
0.84.0 |
ZenML: Write production-ready ML code. |
2025-07-17 03:31:31 |
| abgrouponline |
1.0.4 |
State-of-the-art machine learning models and frameworks for real-world applications - Compatible with all Python versions |
2025-07-16 21:20:11 |
| pokie-score |
0.1.7.dev0 |
Implemenation of the Pokie from Sharief et al. 2025 |
2025-07-15 00:48:23 |
| summit-multi-learn |
0.0.2 |
Supervised MultiModal Integration Tool |
2025-07-11 18:20:42 |
| evokit |
0.2 |
The EvoKit framework, experiment build 1 |
2025-05-24 23:11:34 |
| scaaml |
3.0.4 |
Side Channel Attack Assisted with Machine Learning |
2025-04-09 10:53:17 |
| morphoTreeAdjust |
0.1.4 |
MorphoTreeAdjust is a C++/Python implementation for adjusting the morpholofical trees. |
2025-03-18 11:16:11 |
| gbmframework |
0.2.9 |
A unified framework for Gradient Boosting Models with SHAP analysis |
2025-03-10 23:06:54 |
| neurenix |
1.0.0 |
Empowering Intelligent Futures, One Edge at a Time. |
2025-03-08 01:10:58 |
| deepGreen |
2025.3.2 |
deepGreen: a machine learning based tree-ring width model |
2025-03-03 05:31:05 |
| metatensor-torch |
0.7.2 |
TorchScript bindings for metatensor |
2025-02-18 11:52:34 |
| metatensor-operations |
0.3.2 |
Operations to manipulate metatensor data types |
2025-02-18 09:13:46 |
| scikit-learn-intelex |
2025.2.0 |
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application. |
2025-02-18 08:57:25 |
| pygeoclim |
2025.2.16 |
PyGEOCLIM: GEOCLIM in Python |
2025-02-17 04:30:50 |
| pavimentados |
1.1.0 |
A python package Library which implement IA algorithms to detect cracks and failures on roads. The package is wrapper around all the models and provides an interfaces to use them properly |
2025-02-15 12:50:15 |