Using Deep Learning for Structured Data with Entity Embeddings

In this blog we will touch on two recurring questions in machine learning: The first question revolves around how deep learning performs well on images and text, but how can we use it on our tabular data? Second is a question you must always ask yourself when building a machine learning model: How am I going to deal with categorical variables in this data set? Surprisingly, we can answer both questions with the same answer: entity embeddings. Deep Learning has outperformed other Machine Learning methods on many fronts recently: image recognition, audio classification and natural language processing are just some of the many examples. These research areas all use what is known as'unstructured data', which is data without a predefined structure.