Machine learning has the potential to change the way many businesses operate by enabling real-time predictions and decisions based on deep historical knowledge. However, there is often an impedance mismatch between Data Scientists who generate accurate machine learning models, and IT or Operations departments that need to put these models into production. In this session, Steve will discuss how to harness fast data and stream processing to train, invoke, and potentially automate the retraining of machine learning models. He will walk through real-world, real-time use cases and explain how enabling Data Scientists to work with continuous real-time data can benefit your organisation and eliminate any impedance mismatch that might hinder the operationalising of machine learning.