As ML becomes increasingly important for businesses and data science teams alike, managing its risks is quickly becoming one of the biggest challenges to the technology’s widespread adoption. Join Andrew Bur, Steven Touw, Richard Geering, Joseph Regensburger, and Alfred Rossi for a hands-on overview of how to train, validate, and audit machine learning models (ML) in practice. You’ll learn practical tools and best practices to help safely deploy ML while fully harnessing the technology.
Get in-depth overviews of how ML works in practice and learn best practices for risk management in ML across teams. You’ll focus on understanding both opaque algorithms and large datasets, and how they may adapt and change over time.
In teams, you’ll tackle concrete data science problems to learn how and when ML solves specific problems within the enterprise, how to apply ML to maximize the value of corporate data while minimizing its downsides, and how to manage teams of data scientists engaged in deploying ML within their companies.
You’ll determine the lessons your team learned from their particular use case, then combine these shared insights to illustrate the benefits of a robust risk management framework for ML.
Andrew Burt is chief privacy officer and legal engineer at Immuta, the data management platform for the world’s most secure organizations. He is also a visiting fellow at Yale Law School’s Information Society Project. Previously, Andrew was a special advisor for policy to the head of the FBI Cyber Division, where he served as lead author on the FBI’s after-action report on the 2014 attack on Sony. The leading authority on the intersection between machine learning, regulation and law, Andrew has published articles on technology, history, and law in the New York Times, the Financial Times, Slate, and the Yale Journal of International Affairs. His book, American Hysteria: The Untold Story of Mass Political Extremism in the United States, was called “a must-read book dealing with a topic few want to tackle” by Nobel laureate Archbishop Emeritus Desmond Tutu. Andrew holds a JD from Yale Law School and a BA from McGill University. He is a term-member of the Council on Foreign Relations, a member of the Washington, DC, and Virginia State Bars and a Global Information Assurance Certified (GIAC) cyber incident response handler.
Steve Touw is the cofounder and CTO of Immuta. Steve has a long history of designing large-scale geotemporal analytics across the US intelligence community, including some of the very first Hadoop analytics as well as frameworks to manage complex multitenant data policy controls. He and his cofounders at Immuta drew on this real-world experience to build a software product to make data experimentation easier. Previously, Steve was the CTO of 42Six Solutions (acquired by Computer Sciences Corporation), where he led a large big data services engineering team. Steve holds a BS in geography from the University of Maryland.
Richard Geering is vice president of governance, risk, and compliance at Immuta. He has over 20 years’ experience in the financial services industry, in global leadership roles in risk, sales, and trading in London, New York, and Barbados. Most recently, he was the chief operational risk officer for a global custodian bank. Richard holds a BSc (with honors) in physics from the University of Nottingham.
Joseph Regensburger leads the Research Group at Immuta, where he focuses on model risk management and privacy-preserving machine learning. Previously, he was chief scientist at Illumination Works, LLC and principal research scientist at the Battelle Memorial Institute. Joseph has led research efforts characterizing airport security screening devices, engineering image analysis software, and developing machine learning algorithms for biological detection. He received both Battelle’s Technical Achievement Award and Illumination Works’s Innovation Award. He holds a PhD in physics from the Ohio State University, where his research focused on experimental high-energy physics—specifically the detection of rare decays of D0 mesons.
Alfred Rossi is a theoretical computer scientist and research scientist at Immuta, where his efforts are currently focused on differential privacy and model risk management. His research interests include clustering (especially in alternative settings) and privacy. Alfred holds a PhD in computer science and an MS in physics, both from the Ohio State University.
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