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README.md

Welcome to OpenTabular


OpenTabular is an open research and development organization focused on Tabular Data — combining the strengths of Tabular Deep Learning, Tabular Machine Learning, and Statistical Modeling.

We aim to build high-quality, accessible tools and libraries for working with structured data — from interpretable classical models to state-of-the-art neural methods.

📦 What to Expect

We host a growing collection of repositories, including:

  • 🧠 Deep learning models tailored for tabular data
  • 🤖 Machine learning pipelines and baselines for structured datasets
  • 📈 Statistical and probabilistic tools grounded in tabular modeling
  • 🧪 Experimental hybrids bridging DL, ML, and statistics
  • 🛠️ Utilities for preprocessing, evaluation, visualization, and benchmarking

🤝 Get Involved

If you're working with tabular data — whether as a researcher, engineer, or enthusiast — you're in the right place.
Follow the organization and explore our repositories as we grow the open ecosystem for tabular understanding.

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  1. DeepTab DeepTab Public

    DeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mamb…

    Python 334 29

  2. PreTab PreTab Public

    PreTab is a modular, scikit-learn-compatible representation and preprocessing library for tabular data. Its focus is feature representation and expansion: splines, neural basis maps, piecewise-line…

    Python 19 5

  3. NAMpy NAMpy Public

    Interpretable additive models for tabular data: classical GAMs (with REML smoothness selection, inference, shape constraints & diagnostics) plus neural additive models (NAM, NBM, NodeGAM, GPNAM, SI…

    Python 34 3

Repositories

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Showing 4 of 4 repositories
  • NAMpy Public

    Interpretable additive models for tabular data: classical GAMs (with REML smoothness selection, inference, shape constraints & diagnostics) plus neural additive models (NAM, NBM, NodeGAM, GPNAM, SIAN, SPAM, and more) for regression, classification, and distributional regression.

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    OpenTabular/NAMpy's past year of commit activity
    Python 34 MIT 3 1 0 Updated Nov 10, 2026
  • PreTab Public

    PreTab is a modular, scikit-learn-compatible representation and preprocessing library for tabular data. Its focus is feature representation and expansion: splines, neural basis maps, piecewise-linear encoding, kernel approximations, and language embeddings, each shipped as a standalone transformer that speaks the standard fit / transform.

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    OpenTabular/PreTab's past year of commit activity
    Python 19 MIT 5 0 10 Updated Nov 6, 2026
  • DeepTab Public

    DeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.

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    OpenTabular/DeepTab's past year of commit activity
    Python 334 MIT 29 27 33 Updated Nov 2, 2026
  • .github Public

    General Repository

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    OpenTabular/.github's past year of commit activity
    0 0 0 0 Updated Mar 21, 2025

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