Name | Version | Summary | date |
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 |
iclearn |
0.0.1 |
A collection of utilities for machine learning applications. |
2024-10-18 14:59:09 |
gradio |
5.2.1 |
Python library for easily interacting with trained machine learning models |
2024-10-17 15:29:37 |
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 |
ctreelearn |
0.1.0 |
A simple library for learning of connected filters based on component trees |
2024-10-14 19:46:13 |
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 |
icflow |
0.1.0 |
A collection of simple utilities for machine learning workflows. |
2024-10-08 16:25:24 |
Piscis |
0.2.4 |
An automatic deep learning algorithm for spot detection in fluorescence microscopy images. |
2024-10-05 22:54:08 |
swanlab |
0.3.22 |
Python library for streamlined tracking and management of AI training processes. |
2024-10-05 13:57:47 |
mitosis |
0.5.5 |
Reproduce Machine Learning experiments easily |
2024-10-03 00:13:09 |
PyTimbre |
0.9.6 |
Python conversion of Timbre Toolbox |
2024-10-02 14:39:36 |
nnbma |
1.0.2 |
Neural network-based model approximation (nnbma) |
2024-10-02 11:35:29 |
zenml-nightly |
0.67.0.dev20241002 |
ZenML: Write production-ready ML code. |
2024-10-02 01:01:13 |