  In spite of showing unreasonable effectiveness in modalities like Text and
Image, Deep Learning has always lagged Gradient Boosting in tabular data - both
in popularity and performance. But recently there have been newer models
created specifically for tabular data, which is pushing the performance bar.
But popularity is still a challenge because there is no easy, ready-to-use
library like Sci-Kit Learn for deep learning. PyTorch Tabular is a new deep
learning library which makes working with Deep Learning and tabular data easy
and fast. It is a library built on top of PyTorch and PyTorch Lightning and
works on pandas dataframes directly. Many SOTA models like NODE and TabNet are
already integrated and implemented in the library with a unified API. PyTorch
Tabular is designed to be easily extensible for researchers, simple for
practitioners, and robust in industrial deployments.
