| Name | Version | Summary | date |
| cuery |
0.19.0 |
Prompt (cue) management and execution for tabular data. |
2025-08-23 22:51:51 |
| xrfm |
0.3.1 |
xRFM: Scalable and interpretable kernel methods for tabular data |
2025-08-22 16:18:56 |
| tabm |
0.0.3 |
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling (ICLR 2025). |
2025-08-14 16:14:13 |
| pytabkit |
1.6.1 |
ML models + benchmark for tabular data classification and regression |
2025-08-14 10:49:22 |
| tabcamel |
2025.8.10 |
TabCamel: A DataFrame-focused solution for tabular datasets in machine learning workflows |
2025-08-10 11:40:26 |
| tabeval |
2025.8.10 |
A comprehensive Python framework for evaluating synthetic tabular data generation methods |
2025-08-10 11:30:33 |
| edge-research-pipeline |
1.1.0 |
Modular pipeline for quantitative signal discovery and validation |
2025-08-07 06:38:32 |
| hdx-python-utilities |
3.9.0 |
HDX Python Utilities for streaming tabular data, date and time handling and other helpful functions |
2025-08-05 02:24:12 |
| realtabformer |
0.2.3 |
A novel method for generating tabular and relational data using language models. |
2025-07-14 16:38:30 |
| tabicl |
0.1.3 |
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data |
2025-07-08 09:48:28 |
| dataclr |
0.3.0 |
A Python library for feature selection in tabular datasets |
2025-03-05 22:08:39 |
| pneuma |
0.0.3 |
Pneuma is an LLM-powered data discovery system for tabular data. |
2025-02-26 14:43:57 |
| tab-transformer-pytorch |
0.4.2 |
Tab Transformer - Pytorch |
2025-02-24 00:12:18 |
| hdx-python-scraper |
2.6.3 |
HDX Python scraper utilities to assemble data from multiple sources |
2025-02-18 01:32:12 |
| augini |
0.3.3 |
AI-powered Python framework for tabular data enrichment and analysis using LLMs. Features include intelligent feature engineering, natural language data analysis, and AI agents for automated workflows. |
2025-02-08 17:08:01 |
| ctdGAN |
0.1.9 |
A Generative Adversarial Network for synthesizing artificial tabular data. |
2024-12-26 13:58:22 |
| rtdl_num_embeddings |
0.0.11 |
On Embeddings for Numerical Features in Tabular Deep Learning. |
2024-11-11 21:34:50 |
| be-great |
0.0.8 |
Generating Realistic Tabular Data using Large Language Models |
2024-10-29 16:28:11 |
| tabular-transformer |
0.3.0 |
Transformer adapted for tabular data domain |
2024-09-24 03:22:23 |
| futureframe |
0.2.5 |
Accelerate your data science workflow from months to days with foundation models for tabular data. |
2024-08-29 17:53:57 |