pytorch-widedeep
pytorch-widedeep: A flexible package for multimodal deep learning - Published in JOSS (2023)
flaml
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
autopytorch
Automatic architecture search and hyperparameter optimization for PyTorch
dataset-phenotypes
Preparatory scripts for BIDS tabular phenotypic data in large neuroimaging datasets.
https://github.com/priorlabs/tabpfn-client
⚡ Easy API access to the tabular foundation model TabPFN ⚡
https://github.com/vaexio/vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
caspr
CASPR is a deep learning framework applying transformer architecture to learn and predict from tabular data at scale.
tinto-prueba
TINTO: Software to convert Tidy Data into Image for Classification with 2-Dimensional Convolutional Neural Networks
taulu
Taulu is a Python package designed to segment tabular data in scanned or photographed documents.
ktrain
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
https://github.com/atrcheema/ai4water
framework for developing machine (and deep) learning models for structured data
https://github.com/johnkerl/miller
Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
https://github.com/yandex-research/rtdl
Research on Tabular Deep Learning: Papers & Packages
https://github.com/root-11/tablite
multiprocessing enabled out-of-memory data analysis library for tabular data.
https://github.com/alok-ai-lab/mrep-deepinsight
Multiple Representation DeepInsight technique
https://github.com/astrazeneca/subtab
The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
https://github.com/ajayarunachalam/msda
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
https://github.com/alok-ai-lab/deepinsight3d_pkg
DeepInsight3D package to deal with multi-omics or multi-layered data
https://github.com/SimonBlanke/search-data-explorer
Visualize search-data from your gradient-free-optimization run.
https://github.com/desbordante/desbordante-core
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
https://github.com/calgo-lab/tab_err
Fully-controlled realistic error generation for tabular data.
talent
A comprehensive toolkit and benchmark for tabular data learning, featuring 30+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.
dpl
[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.
https://github.com/cldf/cldf
CLDF: Cross-Linguistic Data Formats - the specification
folktexts
Evaluate uncertainty, calibration, accuracy, and fairness of LLMs on real-world survey data!
ts3l
A PyTorch Lightning-based library for self- and semi-supervised learning on tabular data.
https://github.com/cosbidev/naim
Official implementation for the paper ``Not Another Imputation Method: A Transformer-based Model for Missing Values in Tabular Datasets´´
https://github.com/computationalproteomics/omicloupe
Understanding expression across comparisons and datasets through interactive visualization
https://github.com/clearbox-ai/clearbox-synthetic-kit
Clearbox AI's all-in-one solution for generation and evaluation of synthetic tabular and time-series data.
https://github.com/sebhaan/tabpfgen
TabPFGen: Synthetic Tabular Data Generation with TabPFN