Vector models are being used in a lot of different fields: natural language processing, recommender systems, computer vision, and other things. They are fast and convenient and are often state of the art in terms of accuracy. One of the challenges with vector models is that as the number of dimensions increase, finding similar items gets challenging. Erik developed a library called "Annoy" that uses a forest of random tree to do fast approximate nearest neighbor queries in high dimensional spaces. We will cover some specific applications of vector models with and how Annoy works.
Erik Bernhardsson is the CTO at Better, a small startup in NYC working with mortgages. Before Better, he spent five years at Spotify managing teams working with machine learning and data analytics, in particular music recommendations.