| Name | Version | Summary | date |
| zenml-nightly |
0.84.0.dev20250721 |
ZenML: Write production-ready ML code. |
2025-07-21 00:56:34 |
| crypticorn |
2.19.0 |
Maximise Your Crypto Trading Profits with Machine Learning |
2025-07-20 23:55:37 |
| 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 |
| reax |
0.5.5 |
REAX: A simple training framework for JAX-based projects |
2025-07-20 19:27:50 |
| PyOghma-ML |
0.2.0 |
A Python Pipeline for Machine Learning with Oghma |
2025-07-19 16:19:02 |
| phiml |
1.13.2 |
Unified API for machine learning |
2025-07-19 12:53:53 |
| pet-mad |
1.3.1 |
A universal interatomic potential for advanced materials modeling |
2025-07-18 15:33:19 |
| beast-backbones |
1.1.0 |
Behavioral analysis via self-supervised pretraining of transformers |
2025-07-17 21:44:57 |
| lightning-action |
0.1.0 |
Action segmentation framework built with PyTorch Lightning |
2025-07-17 21:20:44 |
| aenet-gpr |
1.7.6 |
Atomistic simulation tools based on Gaussian Processes Regression |
2025-07-17 20:38:24 |
| nunnpyy |
1.0.0 |
A collection of machine learning algorithms implementations |
2025-07-17 16:01:23 |
| colabfit-kit |
0.0.3 |
A suite of tools for working with training datasets for interatomic potentials |
2025-07-17 14:45:56 |
| swanlab |
0.6.7 |
Python library for streamlined tracking and management of AI training processes. |
2025-07-17 14:43:26 |
| autonomize-model-sdk |
1.1.56 |
SDK for creating and managing machine learning pipelines. |
2025-07-17 14:00:41 |
| 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 |
| featrixsphere |
0.1.595 |
Transform any CSV into a production-ready ML model in minutes, not months. |
2025-07-16 18:29:01 |
| spatialreasoners |
0.1.5 |
SpatialReasoners: A framework for training Spatial Reasoning Models in any domain |
2025-07-16 07:18:05 |
| ntloss |
0.0.2 |
Number Token Loss - A regression-alike loss to improve numerical reasoning in language models |
2025-07-15 21:54:46 |