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What we’re about
Data Science DC is a non-profit professional group that meets monthly to discuss diverse topics in predictive analytics, applied machine learning, statistical modeling, open data, and data visualization. Our members are professionals, students, and others with a deep interest in these fields and related technologies. Meeting topics are varied and range from tutorials on basic concepts and their applications, to success stories from local practitioners, to discussions of tools, new technologies, and best practices. All are welcome -- to attend, to meet others, and to present their work!
Data Science DC is a Program of Data Community DC, Inc.
Upcoming events (2)
See all- Writing a data book: Panel discussionExcella, Arlington, VA
Have you ever wanted to write a book about a data or software topic? Just want to hang out with fun people, come join us at at the Data Science DC panel discussion on writing a data book.
Logistics
This event will be in person. We will try to add an online streaming and recording option if the space, WIFI, and hardware will accommodate, starting at 7pm. Streaming and recording will be on the Data Community DC YouTube channel: youtube.com/@DataCommunityDCAgenda
6:30pm - Food and networking
7:00pm - Talk time
After the talk, some folks will likely head across the street to Courthaus SocialPanelists:
Lauren Maffeo is an award-winning author, analyst, and designer of data systems for U.S. state and federal governments. Her first book, Designing Data Governance from the Ground Up, was published by The Pragmatic Programmers and adapted into a LinkedIn Learning course, with a second course to follow this autumn. Lauren is an Assistant Director of Product on the founding digital services team for the State of Maryland's Family and Medical Leave Insurance (FAMLI), where her team is building the first platform to provide paid caregiver leave in Maryland. She is also an adjunct lecturer of Interaction Design at The George Washington University
Max Tsvetovat is author of Social Network Analysis for Startups - use discount code AUTHD to get 40% off all physical books and 50% off all e-books at O'Reilly - is a professor of Data Science at George Washington University and a Science & Technology Advisor (SETA) at ARPA-H . Most of his career, he has worked in machine learning, modeling and simulation for healthcare and medicine. He's spent 10 years in academia, built and exited two startups, and worked at Google, Humana and Johnson & Johnson. Right now, Max is a "venture socialist", helping the Federal Government invest in cutting edge R&D in healthcare AI.
Peter Gedeck is a data scientist at Collaborative Drug Discovery, where he focuses on the development of novel cheminformatics approaches for drug discovery. He also teaches statistical learning in the School of Data Science at the University of Virginia. In addition to over 50 peer reviewed articles, he co-authored six books. The most popular one is “Practical Statistics for Data Scientists” (O’Reilly) which was translated into eight other languages. The other books are textbooks on machine learning for business analytics and statistics.