tabular-data

React components for efficiently rendering large lists and tabular data

Fast and Accurate ML in 3 Lines of Code

Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

⚡ TabPFN: Foundation Model for Tabular Data ⚡

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

Automatic architecture search and hyperparameter optimization for PyTorch

SDG is a specialized framework designed to generate high-quality structured tabular data.

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains

A unified framework for Deep Learning Models on tabular data

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

A library to model multivariate data using copulas.

Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

A novel approach for synthesizing tabular data using pretrained large language models

A customizable pipeline for multimodal data extraction from MIMIC-IV!

Benchmarking synthetic data generation methods.

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

A comprehensive collection of data quality resources, tools, papers, and projects across various data types including traditional data, LLM pretraining/fine-tuning data, multimodal data, and more. Essential reference for researchers and practitioners in data-centric AI.