14–17 Oct 2019

Yan Zhang
Data Scientist, Microsoft

Yan Zhang is a senior data scientist with the algorithm and data science team of the Data Group within Cloud and Enterprise at Microsoft. She builds predictive analytics models and generalizes machine learning solutions on the cloud machine learning platform. Her recent research includes cost prediction and fraud claim detection in the healthcare domain, predictive maintenance in IoT applications, customer segmentation, and text mining. Previously, she was a research faculty member at Syracuse University. Yan earned her PhD in data mining from the Computer Science Department at the University of Vermont. She’s the author of 23 publications, including journal articles, conference papers, and blog posts. Her first paper won the best paper award at the 17th IEEE International Conference on tools with artificial intelligence. She’s one of the reviewers for the book Predictive Analytics with Microsoft Azure Machine Learning, second edition, published in September 2015.

Sessions

11:05–11:45 Wednesday, 16 October 2019

Location: King's Suite - Sandringham

Deploying machine learning models on the edge

Implementing AI

Secondary topics: Hardware, Machine Learning tools, Mobile Computing, IoT, Edge

Yan Zhang (Microsoft), Mathew Salvaris (Microsoft)

Average rating:

(3.67, 3 ratings)

When IoT meets AI, a new round of innovations begins. Yan Zhang and Mathew Salvaris examine the methodology, practice, and tools around deploying machine learning models on the edge. They offer a step-by-step guide to creating an ML model using Python, packaging it in a Docker container, and deploying it as a local service on an edge device as well as deployment on GPU-enabled edge devices. Read more.