Introducing Machine Learning to a business for the first time

Neill will look back at a project from a decade ago: building and deploying a recommender system for a car rental website. He’ll cover the business problem, the approach he took, the challenges he encountered, and how the system ultimately made it into production. Along the way, \mixture models, stochastic gradient descent, discrete choice modelling, significance testing,\ and \purchasing power parity\ will all make an appearance. Drawing on his experience of taking the project from theory through to implementation, Neill will share some of the things that worked, some that didn’t, and lessons that may help you on your next data science project. --- Neill Sweeney has a B.Sc. in Applied Mathematics, an M.Sc. in Mathematics and Physics, and a Ph.D. in Artificial Intelligence, where he specialised in poker AI. He was interested in AI before it was cool. Since then, he has worked on everything from calibrating milk meters to building recommender systems for car rental websites. He has always been particularly interested in connecting theory with real-world implementation.