Once your machine learning models are set up there’s nothing else to do, right? Wrong, with new tools and trends emerging every year in data science, machine learning is constantly evolving.
In this episode, Manjari Chandran-Ramesh sits down with CEOs from not one but two Amadeus-backed start-ups to discuss the best ways for companies to scale their ML architecture.
Alex Housley, CEO at Seldon, the startup that has developed an open-source machine learning deployment platform and Alberto Rizzoli, CEO at V7, a platform which enables automated labelling, training, and building of AI.
Alex and Alberto consider when to start thinking about scaling ML architecture, explain why moving from a model-centric view of ML to a data-centric one is important and reveal why failures along the way are crucial.