Learning on tabular data

Learning for tabular data, i.e. the stuff you generally store in spreadsheets and relational databases.

Popular in many areas, notably recommender systems.

Not much for now.

(Cheng et al. 2016): jrzaurin/pytorch-widedeep: A flexible package to combine tabular data with text and images using Wide and Deep models in Pytorch. pytorch-widedeep, deep learning for tabular data IV: Deep Learning vs LightGBM

Note that the author of that package advises using gradient boosting machines to get this job done.


Arik, Sercan O., and Tomas Pfister. 2019. TabNet: Attentive Interpretable Tabular Learning,” August.
Cheng, Heng-Tze, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, et al. 2016. Wide & Deep Learning for Recommender Systems.” arXiv:1606.07792 [Cs, Stat], June.
Richetti, Jonathan, Foivos I. Diakogianis, Asher Bender, André F. Colaço, and Roger A. Lawes. 2023. A Methods Guideline for Deep Learning for Tabular Data in Agriculture with a Case Study to Forecast Cereal Yield.” Computers and Electronics in Agriculture 205 (February): 107642.
Shwartz-Ziv, Ravid, and Amitai Armon. 2021. Tabular Data: Deep Learning Is Not All You Need.” arXiv:2106.03253 [Cs], June.

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