David Hershey is a solutions engineer for Determined AI. David has a passion for machine learning infrastructure, in particular systems that enable data scientists to spend more time innovating and changing the world with ML. Previously, David worked at Ford Motor Company as an ML Engineer where he led the development of Ford’s ML platform. He received his MS in Computer Science from Stanford University, where he focused on Artificial Intelligence and Machine Learning.
Despite its enormous potential to enable new applications, deep learning remains prohibitively expensive, difficult, and time-consuming for the vast majority of companies. Training DL models at scale is particularly challenging: training a single model can take days or weeks, and DL engineers are often forced to spend much of their time doing DevOps or writing boilerplate code to handle routine tasks like data loading, distributed training, or fault tolerance.
In this talk, we introduce Determined, an open source platform that enables deep learning teams to train models more quickly, easily share GPU resources, and effectively collaborate. This talk will include an overview of the problems that Determined aims to solve, the high-level architecture of the system, and show how Determined and Spark can be used together effectively. We’ll also dive deep on some key technical features, such as: