Speaker: Mike Conover (LinkedIn)
Title: Building Machine Learning Systems at LinkedIn
Room: Informatics East 122
Abstract: This talk details patterns and machine learning systems to provide our members with actionable, relevant opportunities to nurture their professional networks. Featuring the Connected mobile app as an in-depth case study of how to combine compute-intensive features describing billions of relationships with information that isn’t known until the moment a user opens the app, in this talk we’ll discuss the architectural, modeling, and experimentation patterns leveraged by the Connected relevance team to rank and serve mobile content. Additionally, this session will touch on the human element of machine learning product development, outlining collaboration and communication patterns for working effectively across the organization – from reporting and documentation to evangelism, skills transfer and user experience research. Taken together, these insights will provide a detailed picture of some of LinkedIn’s best practices for building data products at a global scale.
Biography: A graduate of the Indiana University School of Informatics and Computing, Mike Conover builds machine learning technologies that leverage the behavior and relationships of hundreds of millions of people. A senior data scientist at LinkedIn, Mike has a Ph.D. in complex systems analysis with a focus on information propagation in large-scale social networks. His work has appeared in the New York Times, the Wall Street Journal, Forbes, Science, MIT Technology Review and on National Public Radio.