Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Michael Freeman

Michael Freeman
Lecturer, University of Washington

Website | @mf_viz

Michael Freeman is a senior lecturer at the Information School at the University of Washington, where he teaches courses on data science, data visualization, and web development. With a background in public health, Michael works alongside research teams to design and build interactive data visualizations to explore and communicate complex relationships in large datasets. Previously, he was a data visualization specialist and research fellow at the Institute for Health Metrics and Evaluation, where he performed quantitative global health research and built a variety of interactive visualization systems to help researchers and the public explore global health trends. Michael is interested in applications of data visualization to social change. He holds a master’s degree in public health from the University of Washington. You can find samples from his projects on his website.


12:0512:45 Wednesday, 1 May 2019
Secondary topics:  Visualization, Design, and UX
Michael Freeman (University of Washington)
Average rating: ****.
(4.18, 11 ratings)
Statistical and machine learning techniques are only useful when they're understood by decision makers. While implementing these techniques is easier than ever, communicating about their assumptions and mechanics is not. Michael Freeman details a design process for crafting visual explanations of analytical techniques and communicating them to stakeholders. Read more.