Abstract: A series of algorithms can be applied to an automated machine learning model building process in order to reduce complexity and improve model performance. In addition, the settings and parameters for implementing the automated machine learning model building process can be tuned to improve performance of future models. The model building process can also be monitored to ensure that the current build is based on new information compared to previously builds.