Summary The majority of machine learning models have been created and updated in a batch mode. Although this is easy to operate, it doesn’t always give the model’s end consumers the best capabilities or experience. To enable you to respond to real-world events as they happen, Tecton has been investing in the infrastructure and workflows that enable developing and updating ML models with real-time data. In this episode, CTO Kevin Stumpf examines the advantages of real-time machine learning and the technologies required to support its creation and upkeep.
