14–17 Oct 2019

Wee Hyong Tok
Principal Data Science Manager, Microsoft

Wee Hyong Tok is a principal data science manager with the AI CTO Office at Microsoft, where he leads the engineering and data science team for the AI for Earth program. Wee Hyong has worn many hats in his career, including developer, program and product manager, data scientist, researcher, and strategist, and his track record of leading successful engineering and data science teams has given him unique superpowers to be a trusted AI advisor to customers. Wee Hyong coauthored several books on artificial intelligence, including Predictive Analytics Using Azure Machine Learning and Doing Data Science with SQL Server. Wee Hyong holds a PhD in computer science from the National University of Singapore.

Sessions

9:00–12:30 Tuesday, 15 October 2019

Location: Windsor Suite

Training and deploying Python models on Azure

Implementing AI

Secondary topics: Computer Vision, Machine Learning, Machine Learning tools

Danielle Dean (iRobot), Mathew Salvaris (Microsoft), Wee Hyong Tok (Microsoft)

Average rating:

(4.33, 6 ratings)

Danielle Dean, Mathew Salvaris, and Wee Hyong Tok outline the recommended ways to train and deploy Python models on Azure, ranging from running massively parallel hyperparameter tuning using Hyperdrive to deploying deep learning models on Kubernetes. Read more.

14:35–15:15 Wednesday, 16 October 2019

Location: King's Suite - Sandringham

Azure AI reference architectures

Implementing AI

Secondary topics: Machine Learning, Machine Learning tools

Danielle Dean (iRobot), Wee Hyong Tok (Microsoft), Mathew Salvaris (Microsoft)

Average rating:

(4.00, 2 ratings)

Dive into the the newly released GitHub repository for recommended ways to train and deploy models on Azure with Danielle Dean, Wee Hyong Tok, and Mathew Salvaris. The repository ranges from running massively parallel hyperparameter tuning using Hyperdrive to deploying deep learning models on Kubernetes. Read more.