Practical machine learning (ML) is a trial and error process. ML practitioners compare different performance metrics by running ML experiments till you find the best model with a given set of parameters. Because of the experimental nature of ML, there are many reasons for tracking ML experiments and making them reproducible including debugging and compliance. But tracking experiments is challenging: you need to organize experiments so that other team members can quickly understand, reproduce and compare them. That adds overhead that you don't need.

Machine learning (ML) is essential to video game development. Predicting specific in-game actions and identifying and reaching your most valuable players helps to drive better outcomes. To this end, we need to keep track of all experiments that are happening behind the scenes. Google Cloud recently announced the general availability of a new feature called Vertex AI Experiments that can now help gaming companies do just that – keep track of their ML experiments to uncover insights and best practices across their ML Engineering and Data Science teams. In this blog post, we will focus on a popular video game dataset coming from the EA Sports' FIFA video game series.