tusharsarkar3/XBNet
Boosted neural network for tabular data
This project helps data scientists and machine learning engineers build more accurate and interpretable predictive models from spreadsheet-like data. It takes your structured datasets as input and produces a boosted neural network model that can make predictions. This is ideal for professionals working with tabular data who need robust classification or regression solutions.
217 stars. No commits in the last 6 months.
Use this if you need to build highly accurate predictive models for tabular data and want better performance and interpretability than traditional methods.
Not ideal if your data is unstructured (like images, text, or audio) or if you require extremely fast model inference on very large datasets without any setup.
Stars
217
Forks
47
Language
Python
License
MIT
Category
Last pushed
Jul 25, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/tusharsarkar3/XBNet"
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