This Guidance demonstrates how to implement an automated machine learning (ML) pipeline to gain real-time player insights, powered by artificial intelligence (AI), enabling studios to better understand player behavior and improve the overall game experience. Game studios can leverage this low-code solution to quickly build, train, and deploy high-quality models that predict player behavior using their own gameplay data. Operators simply upload player data to Amazon Simple Storage Service (Amazon S3), which invokes an end-to-end workflow to extract insights, select algorithms, tune hyperparameters, evaluate models, and deploy the best performing model to a prediction API. This automated process requires no manual machine learning tasks while delivering real-time predictions that give studios valuable insights into individual player retention, engagement, and monetization to inform data-driven decisions that improve gameplay.