An Introduction to Deep Learning for Tabular Data

There is a powerful technique that is winning Kaggle competitions and is widely used at Google (according to Jeff Dean), Pinterest, and Instacart, yet that many people don’t even realize is possible: the use of deep learning for tabular data, and in particular, the creation of embeddings for categorical variables.
Despite what you may have heard, you can use deep learning for the type of data you might keep in a SQL database, a Pandas DataFrame, or an Excel spreadsheet (including time-series data). I will refer to this as tabular data, although it can also be known as relational data, structured data, or other terms (see my twitter poll and comments for more discussion).

  

From the Pinterest blog post 'Applying deep learning to Related Pins'

Tabular data is the most commonly used type of data in industry, but deep learning on tabular data receives far less attention than deep learning for computer vision and natural language processing. 

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