| Name | Version | Summary | date |
| mlblocks |
0.6.1 |
Pipelines and primitives for machine learning and data science. |
2023-09-26 17:42:09 |
| molzip |
0.9.1 |
An implementation of compression-based regression and classification for molecular SMILES. |
2023-09-25 20:19:04 |
| classgraphic |
0.3.1 |
Interactive classification diagnostic plots |
2023-09-21 13:01:49 |
| pyracer |
1.2.1 |
Unofficial Python implementation of the RACER classification algorithm. |
2023-09-12 20:16:52 |
| demv |
1.0.1 |
Debiaser for Multiple Variables(DEMV) is a pre-processing algorithm for binary and multi-class datasets that mitigates bias by perfectly balancing the sensitive groups identified by each possible sensitive variables' value and each label's value |
2023-09-12 13:04:55 |
| xai-kit |
0.0.7 |
Explainable Artificial Intelligence (XAI) Library |
2023-09-10 23:25:22 |
| gecs |
0.1.1 |
LightGBM Classifier with integrated bayesian hyperparameter optimization |
2023-09-10 09:29:08 |
| xaiz |
0.0.3 |
Explainable Artificial Intelligence (XAI) Library |
2023-09-09 17:29:21 |
| blitzml |
0.20.0 |
A low-code library for machine learning pipelines |
2023-08-25 12:11:05 |
| pytransformers |
0.1.0 |
create transformer models (Architecture behind chat GPT and other large language models) |
2023-08-12 16:29:58 |
| happytransformer |
3.0.0 |
Happy Transformer makes it easy to fine-tune NLP Transformer models and use them for inference. |
2023-08-05 22:54:04 |
| baytune |
0.5.0 |
Bayesian Tuning and Bandits |
2023-07-28 16:54:26 |
| owl-results |
0.1.4 |
Manipulate Complex OWL Parse Results |
2023-07-26 18:23:14 |
| discovery-transition-ds |
4.18.14 |
Data Science to production accelerator |
2023-07-03 15:30:54 |
| Categorium |
0.0.1 |
Package with trained language models in 6 differente languages. |
2023-06-28 17:06:43 |
| fast-sentence-tokenize |
0.1.15 |
Fast and Efficient Sentence Tokenization |
2023-06-27 19:14:02 |
| classically |
1.0.4 |
Classifier Comparison and Feature Analysis Tools in Python |
2023-06-27 14:12:20 |
| SmplML |
1.0.6 |
SmplML is a user-friendly Python module for streamlined machine learning classification and regression. It offers intuitive functionality for data preprocessing, model training, and evaluation. Ideal for beginners and experts alike, SmplML simplifies ML tasks, enabling you to gain valuable insights from your data with ease. |
2023-06-13 04:33:47 |
| tabular-ml |
0.0.2 |
This library wraps popular tabular regression/classification model enabling rapid evaluation and optimization. |
2023-06-05 19:33:38 |
| codcat |
0.2.0 |
Code snippets language classification tool |
2023-06-05 11:30:15 |