Today, we’re pleased to announce that Amazon SageMaker Autopilot has added a new training mode that supports model ensembling powered by AutoGluon. For moderately large datasets (< 100MB), ensemble training mode builds machine learning (ML) models with high accuracy quickly – up to 8x faster than the current hyper parameter optimization (HPO) training mode with 250 trials. Amazon SageMaker Autopilot automatically builds, trains, and tunes the best ML models based on your data, while allowing you to maintain full control and visibility. The current HPO mode uses a combination of hyper parameter values to maximize the accuracy of a single model. However, in cases when a single model is unable to capture the complex characteristics of data, combining (or ensembling) the predictions from diverse models can significantly improve overall model accuracy.