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

Autogluon ⭐ 7,109

Fast and Accurate ML in 3 Lines of Code

Flaml ⭐ 3,500

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

Tabnet ⭐ 2,386

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

Lightning Flash ⭐ 1,730

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

Dataprofiler ⭐ 1,310

What's in your data? Extract schema, statistics and entities from datasets

Ydata Synthetic ⭐ 1,201

Synthetic data generators for tabular and time-series data

Ktrain ⭐ 1,188

ktrain is a Python library that makes deep learning and AI more accessible and easier to apply

Pytorch_tabular ⭐ 1,138

A standard framework for modelling Deep Learning Models for tabular data

Awesome Fl ⭐ 1,103

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

Aws Machine Learning University Accelerated Tab ⭐ 931

Machine Learning University: Accelerated Tabular Data Class

Copulas ⭐ 454

A library to model multivariate data using copulas.

Gan For Tabular Data ⭐ 442

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

Deltapy ⭐ 411

DeltaPy - Tabular Data Augmentation (by @firmai)

Carefree Learn ⭐ 400

Deep Learning ❤️ PyTorch

Synthcity ⭐ 292

A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.

Tableqa ⭐ 254

AI Tool for querying natural language on tabular data.

Aws Machine Learning University Dte ⭐ 177

Machine Learning University: Decision Trees and Ensemble Methods

Automl_alex ⭐ 171

State-of-the art Automated Machine Learning python library for Tabular Data

Tabular Dl Tabr ⭐ 166

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

Machine Learning Roadmap ⭐ 149

A roadmap for getting started with Machine Learning

Tabformer ⭐ 144

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

Transtab ⭐ 140

NeurIPS'22 | TransTab: Learning Transferable Tabular Transformers Across Tables

Lamda Ssl ⭐ 130

30 Semi-Supervised Learning Algorithms

Awesome Self Supervised Learning For Tabular Data ⭐ 71

A collection of research materials on SSL for tabular data

Gatedtabtransformer ⭐ 63

A deep learning tabular classification architecture inspired by TabTransformer with integrated gated multilayer perceptron.

Ai4water ⭐ 46

framework for developing machine (and deep) learning models for structured data

Autotabular ⭐ 45

Automatic machine learning for tabular data. ⚡🔥⚡

Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN

Ml Workflow ⭐ 35

A hands-on case study for demonstrating the stages involved in a machine learning project, from EDA to production.

Familiar ⭐ 27

Repository for the familiar R-package. Familiar implements an end-to-end pipeline for interpretable machine learning of tabular data.

Vevestax ⭐ 24

2 Lines of code to track ML experiments + EDA + check into Github

Library of composable generative population models which serve as the modeling and inference backend of BayesDB.

Easy formatted text extraction from images using Google Vision API

T2g Former ⭐ 15

Original implementation and experiment results of T2G-FORMER

MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs.

Open-source version of the TDspora synthetic data generation algorithm.

Imodels Experiments ⭐ 13

Experiments with experimental rule-based models to go along with imodels.

Multiaug ⭐ 12

Multi-modal data augmentation for machine learning

Tabular Dl Pretrain Objectives ⭐ 10

Revisiting Pretrarining Objectives for Tabular Deep Learning

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

Cookiecutter Ml Research ⭐ 7

A logical, reasonably standardized, but flexible project structure for conducting ml research.

LightGBM + Optuna

The official implementation of the paper "Rethinking Data Augmentation for Tabular Data in Deep Learning"

Acupoftea ⭐ 5

Let's settle down, rest our minds, spill the tea of our experience in multiple ai fields [Data Science, Machine Learning, Deep Learning], including many other aspects starting from prorgramming and clean code till design patterns & businness interference. Enjoy the drink, and if you find something interesting here, offer us a cup of tea.

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