Talk abstract: Machine learning and artificial intelligence are helping solve some of the most challenging problems today. The iterative process typically starts with a problem statement, followed by data acquisition, modeling and deployment. Although there is an abundance of tools and libraries that help practitioners build models, deployment can sometimes be a challenge. In this session attendees will be introduced to Microsoft's cross-platform open source machine learning framework ML.NET which we'll use to dive into the full process of building a machine learning model from scratch. We'll then take our trained model and explore two ways of deploying it to Azure via containers and serverless functions.
Speaker: Luis Quintanilla is an Artificial Intelligence Consultant based out of New York with experience in machine learning and software development. He spent a few years in the financial services industry in a full stack analytics developer role and currently partners with clients to help guide them through their Artificial Intelligence adoption journey by building end-to-end solutions that push the edge of what's possible. Although in such projects he utilizes the tool that gets the job done, he has a personal preference for the Microsoft ecosystem.
11 Times Square (NE Corner of 41st St and 8th Ave)