| Name | Version | Summary | date |
| deepGreen |
2025.3.2 |
deepGreen: a machine learning based tree-ring width model |
2025-03-03 05:31:05 |
| maite |
0.7.3 |
Library of common types, protocols (a.k.a. structural subtypes), and utilities to support AI test and evaluation |
2025-02-19 19:43:05 |
| 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 |
| metatensor-core |
0.1.12 |
Python bindings for metatensor |
2025-02-18 07:26:31 |
| 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 |
| rdt |
1.14.0 |
Reversible Data Transforms |
2025-02-12 02:14:26 |
| RapidUseML |
1.0.2 |
Minimalistic Machine Learning Toolset. |
2025-02-09 17:26:08 |
| gurulearn |
2.0.2 |
Comprehensive ML library for model analysis, computer vision, medical imaging, and audio processing with enhanced features including confidence metrics and flowbot integration (bug fixes) |
2025-02-09 06:53:54 |
| modelib |
0.3.0 |
A minimalist framework for online deployment of sklearn-like models |
2025-02-07 18:30:49 |
| sdgym |
0.10.0 |
Benchmark tabular synthetic data generators using a variety of datasets |
2025-02-07 02:37:02 |
| bandit-agents |
0.5.23 |
Library to solve k-armed bandit problems |
2025-02-06 23:27:32 |
| equine-webapp |
0.1.dev82 |
Companion web application for EQUINE^2: Establishing Quantified Uncertainty for Neural Networks |
2025-02-06 21:54:56 |
| phiml |
1.12.2 |
Unified API for machine learning |
2025-02-06 17:22:48 |
| SFOF4S |
1.0.13 |
This toolkit aids in analyzing drop sliding on tilted plates, allowing researchers to study various variables and their correlations in detail. |
2025-02-06 00:02:26 |
| imbalanced-learn-extra |
0.2.9 |
An implementation of novel oversampling algorithms. |
2025-02-05 17:05:36 |
| ximilar-client |
1.37.0 |
The Ximilar App and Vize.ai Client. |
2025-02-04 15:05:49 |
| metatensor-learn |
0.3.1 |
Building blocks for the atomistic machine learning models based on PyTorch and NumPy |
2025-02-03 16:26:12 |