Data Visualization for Machine Learning

Lecture / Panel
For NYU Community

Speakers:   Fernanda Viégas and Martin Wattenberg, Google

Title:  Data Visualization for Machine Learning


Machine learning is playing an increasingly influential role in the world, due to dramatic technical leaps in recent years. But these new developments bring their own questions. How can we understand what is going on under the hood of deep neural networks? How can we better debug these systems? How can we broaden the conversation about ML-enabled automated decision making? It turns out that visualization can play a central role in answering these questions. We'll discuss recent work that shows how interactive exploration can help people use, interpret, and learn about machine intelligence.


Fernanda Viégas and Martin Wattenberg co-lead Google’s PAIR (People+AI Research) initiative, part of Google Brain. Their work in machine learning focuses on transparency and interpretability, as part of a broad agenda to improve human/AI interaction. They are well known for their contributions to social and collaborative visualization, and the systems they’ve created are used daily by millions of people. Their visualization-based artwork has been exhibited worldwide, and is part of the permanent collection of Museum of Modern Art in New York.