Fast and Accurate ML in 3 Lines of Code
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Updated
May 31, 2024 - Python
Fast and Accurate ML in 3 Lines of Code
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
Automatic architecture search and hyperparameter optimization for PyTorch
Conditional GAN for generating synthetic tabular data.
A terminal spreadsheet multitool for discovering and arranging data
Algorithms for outlier, adversarial and drift detection
Your PyTorch AI Factory - Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
What's in your data? Extract schema, statistics and entities from datasets
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
A common, beautiful interface to tabular data, no matter the format
A standard framework for modelling Deep Learning Models for tabular data
DeepTables: Deep-learning Toolkit for Tabular data
AI code-writing assistant that understands data content
A library to model multivariate data using copulas.
Research on Tabular Deep Learning: Papers & Packages
Implementation of TabTransformer, attention network for tabular data, in Pytorch
Generative adversarial training for generating synthetic tabular data.
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