Modern Deep Learning for Tabular Data: Novel Approaches to Common Modeling Problems

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

A. Ye, Z. WangModern Deep Learning for Tabular Datahttps://doi.org/10.1007/978-1-4842-8692-0_4

4. Applying Convolutional Structures to Tabular Data

Andre Ye¹   and Zian Wang²

(1)

Seattle, WA, USA

(2)

Redmond, WA, USA

 

There are things known and there are things unknown, and in between are the doors of perception.

—Aldous Huxley, Writer and Philosopher

In the previous chapter, you explored the application of standard feed-forward/artificial neural network models to tabular data. In this chapter, we will take a significant jump from the well-documented and “traditional” into the new and comparatively uncharted by exploring the application of convolutional structures ...