Automated Machine Learning with Explainability

ML has revolutionized a large range of industry applications with new techniques for consuming complex data modalities, such as images and text. However, for a given dataset and business use case, non-technical users are faced by adoption limiting questions, like which model should I use and how should I set its hyper-parameters. This is challenging and time consuming even for seasoned data scientists. The AutoMLx team at Oracle Labs has developed an automated machine learning pipeline with explainability tools built-in for novice and advanced users. In this talk, we provide an overview of our current and upcoming AutoMLx features and some applications; for example, how to predict construction site delays and how to forecast CPU resource usage based on previous consumption trends.