This chapter covers
- What tabular data is
- Why tabular data matters
- The distinction between deep learning andnon-deep learning approaches to tabular data
- What people think about using deep learning with tabular data
- Characteristics of tabular data that distinguish it from other kinds of data, like image, sound, or text data
Tabular data is central to our modern lives and, for most of us, to our work lives. Tabular data exists in spreadsheets as CSV files and in the tables of relational databases, it populates analysis and reports, and it can be the fuel for training machine learning models. Machine learning models trained on your tabular business can successfully solve many useful problems, such as predicting inventory requirements in retail outlets or predicting the price of market commodities.
In this chapter, we introduce the process of selecting the appropriate modeling approach for tabular data problems. We present two main approaches: deep learning and classical machine learning. Then, from the data perspective, we look at some of the unique considerations you face when using tabular data with machine learning models.