“Building accurate recommendation models has traditionally been one of the hardest problems in Machine Learning (ML), and few organizations have had the knowledge, skills, and experience to overcome these challenges. For over 20 years, Amazon.com has built recommender systems at scale, integrating personalized recommendations across the buying experience – from product discovery to checkout. Using this experience, Amazon Web Services (AWS) has built cloud-based services that put personalization and recommendation in the hands of organizations with little or no ML experience. In this session, we’ll show you how to quickly get started, and what AWS customers have built on their own.”
As the Global AI & Machine Learning Evangelist, Julien focuses on helping developers and enterprises bring their ideas to life. He frequently speaks at conferences, and also actively blogs on the AWS Blog and Medium.
Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in top-tier web startups where he led large Software and Ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations and how cloud computing can help.