| Name | Version | Summary | date |
| sklearn2c |
0.0.2 |
A simple tool to embed scikit-learn models into microcontrollers |
2024-06-16 18:47:51 |
| sklearn-smithy |
0.2.0 |
Toolkit to forge scikit-learn compatible estimators. |
2024-06-15 20:32:04 |
| niceml |
0.16.0 |
Welcome to niceML 🍦, a Python-based MLOps framework that uses TensorFlow and Dagster. This framework streamlines the development, and maintenance of machine learning models, providing an end-to-end solution for building efficient and scalable pipelines. |
2024-06-13 09:44:40 |
| NiaAML |
2.1.0 |
Python automated machine learning framework |
2024-06-12 12:19:11 |
| skfolio |
0.2.2 |
Portfolio optimization built on top of scikit-learn |
2024-06-04 22:50:13 |
| sktime |
0.30.0 |
A unified framework for machine learning with time series |
2024-06-03 23:23:03 |
| NiaAML-GUI |
0.3.1 |
GUI for NiaAML Python package |
2024-06-02 10:04:40 |
| aeon |
0.9.0 |
A toolkit for machine learning from time series |
2024-05-31 20:12:11 |
| haupt |
2.2.0 |
Lineage metadata API, artifacts streams, sandbox, ML-API, and spaces for Polyaxon. |
2024-05-28 16:44:22 |
| felimination |
0.2.3 |
This library contains some useful scikit-learn compatible classes for feature selection. |
2024-05-28 09:30:13 |
| skpro |
2.3.1 |
A unified framework for probability distributions and probabilistic supervised regression |
2024-05-26 06:33:56 |
| scikit-base |
0.8.0 |
Base classes for sklearn-like parametric objects |
2024-05-25 20:11:45 |
| shogunfolio |
0.1.0 |
Portfolio optimization built on top of scikit-learn |
2024-05-25 17:55:11 |
| positional-vectorizer |
0.0.9 |
Positional Vectorizer is a scikit-learn transformer that converts text to bag of words vector using a positional ranking algorithm as score |
2024-05-21 23:41:22 |
| AutogluonToScikitWrapper |
0.0.1 |
Autogluon to Scikit Wrapper |
2024-05-16 12:00:05 |
| scikit-learn-intelex |
2024.4.0 |
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application. |
2024-05-13 17:41:22 |
| daal4py |
2024.4.0 |
daal4py is a Convenient Python API to the Intel® oneAPI Data Analytics Library (oneDAL) |
2024-05-13 17:35:40 |
| mlrl-boomer |
0.10.0 |
A scikit-learn implementation of BOOMER - an algorithm for learning gradient boosted multi-label classification rules |
2024-05-05 17:02:39 |
| mlrl-seco |
0.10.0 |
A scikit-learn implementation of a separate-and-conquer multi-label rule learning algorithm |
2024-05-05 17:01:59 |
| mlrl-common |
0.10.0 |
Provides common modules to be used by different types of multi-label rule learning algorithms |
2024-05-05 17:01:31 |