Danielle Dean, Technical Director of Machine Learning at iRobot, presents the “Optimizing ML Systems for Real-World Deployment” tutorial at the May 2021 Embedded Vision Summit.
In the real world, machine learning models are components of a broader software application or system. In this talk, Dean explores the importance of optimizing the system as a whole–not just optimizing individual ML models.
Based on experience building and deploying deep-learning-based systems for one of the largest fleets of autonomous robots in the world (the Roomba!), Dean highlights critical areas requiring attention for system-level optimization, including data collection, data processing, model building, system application and testing. She also shares recommendations for ways to think about and achieve optimization of the whole system.
See here for a PDF of the slides.