zadid6pretam/TabSeq
TabSeq: A Framework for Deep Learning on Tabular Data via Sequential Ordering
This framework helps data scientists and machine learning engineers apply advanced deep learning techniques to complex tabular datasets for classification tasks. It takes raw tabular data, processes it by intelligently ordering features, and outputs highly accurate predictions for either binary or multi-class scenarios. The goal is to improve predictive model performance on datasets commonly found in health informatics or financial modeling.
No commits in the last 6 months. Available on PyPI.
Use this if you are a data scientist struggling to get high performance from deep learning models on tabular data, especially when features are diverse or have hidden relationships.
Not ideal if you primarily work with image or text data, or if you prefer traditional machine learning methods over deep learning for tabular problems.
Stars
10
Forks
—
Language
Python
License
MIT
Category
Last pushed
Jul 21, 2025
Commits (30d)
0
Dependencies
5
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/zadid6pretam/TabSeq"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
PriorLabs/TabPFN
⚡ TabPFN: Foundation Model for Tabular Data ⚡
pyg-team/pytorch-frame
Tabular Deep Learning Library for PyTorch
NVIDIA-Merlin/NVTabular
NVTabular is a feature engineering and preprocessing library for tabular data designed to...
PriorLabs/tabpfn-extensions
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
pytorch-tabular/pytorch_tabular
A unified framework for Deep Learning Models on tabular data