Alexander Wang

Automated feature engineering solves one of the biggest problems in applied machine learning by streamlining a critical, yet manually intensive step in the ML pipeline. However, even after feature engineering, handling non-numeric data for use by machine learning algorithms is unavoidable and presents its own set of unique challenges. This