Chang Liu
Applied Research Scientist, Georgian Partners

Chang Liu is an applied research scientist at Georgian Partners and a member of the Georgian impact team, where she draws on her in-depth knowledge of mathematical and combinatorial optimization to help Georgian’s portfolio companies. Previously, Chang was a risk analyst at Manulife Bank, where she built models to assess the bank’s risk exposure based on extensive market research, including evaluating and predicting the impact of the oil price drop to the mortgage lending risks in Alberta in 2014. Chang holds a master of applied science in operations research from the University of Toronto, where she specialized in combinatorial optimization, and a bachelor’s degree in mathematics from the University of Waterloo.

Sessions

11:55–12:35 Wednesday, 16 October 2019

Location: Blenheim Room - Palace Suite

Building differentially private machine learning models using TensorFlow

Models and Methods

Secondary topics: Ethics, Security, and Privacy, Machine Learning, Machine Learning tools

Chang Liu (Georgian Partners ), Ji Chao Zhang (Georgian Partners)

Average rating:

(4.33, 3 ratings)

The world is increasingly data driven, and people have developed an awareness and concern for their data. Chang Liu and Ji Chao Zhang examine differential privacy—the component of the TensorFlow Privacy library that allows users to train differentially private logistic regression and support vector machines—along with real-world use cases and demonstrations for how to apply the tools. Read more.