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Designing and Implementing Production Machine Learning Systems

Kyle Gallatin
Data Science Academy Mentor
Panelist Spotlight

Kyle Gallatin is currently a software engineer on the machine learning platform team at Etsy. In this role, Kyle is redesigning existing ML systems with a focus on ML model training, real-time model serving, MLOps processes, and model governance. Kyle spends his free time teaching and volunteering within the ML space. He also writes articles for technical publications on ML engineering, MLOps, and infrastructure.

In this event, Kyle Gallatin will give an introduction to his upcoming course: "Designing and Implementing Production Machine Learning Systems". He will discuss the requirements for registering in the course, the content that will be covered, and the skills that students will walk away with.   About This Event As machine learning (ML) becomes ubiquitous in technology, there is an increasing need for well-engineered ML systems and processes that enable ML algorithms to drive business value. Enterprise ML has experienced a shift in focus from just the ML models themselves to the software engineering, infrastructure and best practices necessary to support ML at scale in production. Bringing a model from a data scientist's notebook to running live in an application requires robust systems, MLOps and ML governance.