| Name | Version | Summary | date |
| toyml |
0.3.2 |
ToyML: Machine Learning from Scratch |
2024-10-25 06:25:45 |
| scaleup-optimizer |
1.0.0 |
This library is use to optimize hyperparameter of machine learning with scale up algorithm |
2024-10-25 04:07:22 |
| zenml |
0.68.0 |
ZenML: Write production-ready ML code. |
2024-10-24 23:35:09 |
| mitosis |
0.5.6 |
Reproduce Machine Learning experiments easily |
2024-10-24 21:23:46 |
| metatensor-core |
0.1.11 |
Python bindings for metatensor |
2024-10-24 10:40:21 |
| ctreelearn |
0.1.7 |
A simple library for learning of connected filters based on component trees |
2024-10-23 13:39:54 |
| gradio |
5.3.0 |
Python library for easily interacting with trained machine learning models |
2024-10-22 02:47:32 |
| sparrow-python |
0.2.7.2 |
None |
2024-10-21 17:00:11 |
| iclearn |
0.0.2 |
A collection of utilities for machine learning applications. |
2024-10-21 13:51:39 |
| swanlab |
0.3.23 |
Python library for streamlined tracking and management of AI training processes. |
2024-10-21 06:39:15 |
| ml-experiment |
0.0.9 |
Machine Learning Experiment Framework |
2024-10-18 17:09:51 |
| phiml |
1.9.3 |
Unified API for machine learning |
2024-10-18 15:39:37 |
| hep-ml |
0.7.3 |
Machine Learning for High Energy Physics |
2024-10-16 21:52:19 |
| maite |
0.6.1 |
Library of common types, protocols (a.k.a. structural subtypes), and utilities to support AI test and evaluation |
2024-10-16 13:02:58 |
| evokit |
0.1 |
The EvoKit framework, experiment build 1 |
2024-10-16 01:55:12 |
| outlines |
0.1.1 |
Probabilistic Generative Model Programming |
2024-10-15 12:55:26 |
| qoa4ml |
0.3.16 |
Quality of Analysis for Machine Learning |
2024-10-15 10:40:02 |
| metatensor-operations |
0.2.4 |
Operations to manipulate metatensor data types |
2024-10-14 09:37:03 |
| mlrose-ky |
1.1.6 |
MLROSe-ky: Machine Learning, Randomized Optimization and Search |
2024-10-12 22:21:51 |
| rdt |
1.13.0 |
Reversible Data Transforms |
2024-10-08 21:44:57 |