dreamquark-ai/tabnet
A PyTorch library implementing TabNet, an attention-based deep learning model designed for tabular data classification and regression tasks.
Not currently ranked — collecting fresh signals.
star history
TabNet provides a PyTorch implementation of the TabNet architecture, which uses sequential attention to choose which features to reason from at each decision step. The model combines the interpretability of decision trees with the representational power of deep neural networks, enabling both high accuracy on tabular data and feature importance insights through its attention mechanism. It is distributed via pip and conda as pytorch-tabnet.
Frequently asked
- What is dreamquark-ai/tabnet?
- A PyTorch library implementing TabNet, an attention-based deep learning model designed for tabular data classification and regression tasks.
- Is tabnet open source?
- Yes — dreamquark-ai/tabnet is open source, released under the MIT license.
- What language is tabnet written in?
- dreamquark-ai/tabnet is primarily written in Python.
- How popular is tabnet?
- dreamquark-ai/tabnet has 3k stars on GitHub.
- Where can I find tabnet?
- dreamquark-ai/tabnet is on GitHub at https://github.com/dreamquark-ai/tabnet.