| Name | Version | Summary | date |
| Blauwal3-Network |
1.9.0 |
用于网络的蓝鲸数据挖掘附加组件。 |
2024-09-30 09:58:38 |
| Blauwal3 |
3.38.5 |
蓝鲸，一个基于组件的数据挖掘框架。 |
2024-09-27 12:17:39 |
| pypots |
0.8.1 |
A Python Toolbox for Machine Learning on Partially-Observed Time Series |
2024-09-26 05:57:24 |
| perplexity-correlations |
0.1.2 |
Simple and scalable tools for great pretraining data selection. |
2024-09-19 21:57:55 |
| pyrlutils |
0.0.3 |
Utility and Helpers for Reinformcement Learning |
2024-09-18 03:07:07 |
| ai4ts |
0.0.3 |
AI for Time Series |
2024-09-14 02:08:54 |
| sparks-ai |
0.1.1 |
Sequential Predictive Attention for the Representation of SpiKing Signals |
2024-09-12 10:24:32 |
| ArticutAPI-Taigi |
0.95 |
Articut NLP system provides not only finest results on Chinese word segmentaion (CWS), Part-of-Speech tagging (POS) and Named Entity Recogintion tagging (NER), but also the fastest online API service in the NLP industry. |
2024-09-09 15:53:37 |
| civitai-models-manager |
0.8.5 |
CLI tool for managing AI models from the CivitAI platform. |
2024-09-08 14:41:56 |
| TimeSeriesAI |
0.0.0 |
AI for Time Series |
2024-09-07 16:53:00 |
| needle-haystack-ai |
0.1.0 |
Needle RAG tools for Haystack |
2024-08-29 10:24:26 |
| scikit-activeml |
0.5.2 |
Our package scikit-activeml is a Python library for active learning on top of SciPy and scikit-learn. |
2024-08-28 16:01:25 |
| datasu |
0.1.1 |
Essential utilities for data scientists |
2024-08-28 08:01:50 |
| opipy-pm |
0.1.3 |
OPI Solutions Python package for Predictive Maintenance |
2024-08-27 19:36:17 |
| tensortrade-ng |
2.0.0a1 |
TensorTrade-NG: A reinforcement learning library for training, evaluating, and deploying robust trading agents. |
2024-08-26 11:24:14 |
| stylegan2-pytorch |
1.8.11 |
StyleGan2 in Pytorch |
2024-08-23 17:16:04 |
| slot-attention |
1.4.0 |
Implementation of Slot Attention in Pytorch |
2024-08-20 18:35:29 |
| TfELM |
1.1 |
This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning algorithm known for their simplicity, efficiency, and scalability, making them ideal for various applications, including classification, regression, and feature learning tasks. |
2024-08-20 09:28:42 |
| benchpots |
0.2.2 |
A Python Toolbox for Benchmarking Machine Learning on Partially-Observed Time Series |
2024-08-14 17:38:01 |
| protectai |
1.0.3 |
Simulation of protecting AI model from poisoning attack |
2024-08-13 17:42:33 |