Data Science DC

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!

Upcoming Events:

  • Big Graph Data Science
  • Machine Learning on Distributed Data; p-Tree Algebra
  • Lightning Talks at PAW-Gov

Tentative Events:

  • Agent-Based Modeling
  • Apophenia and Probabilistic Programming
  • The Trouble with P-Values
  • Multiple Regression with Poststratification
  • Data Intensive Science at Extreme Scale
  • Intro to Digital Humanities
  • eDiscovery
  • Statistical Literacy and Secondary Statistics Education
  • Govtrack analyses
  • Topic Modeling
  • Statistical Methods for Establishing Trust in Crowd Sourced Data
  • Topic Analysis of Scams
  • Data Security
  • Washington Nationals
  • Optimizing the Red Cross
  • Mining Childhood Cancer Data
  • Persuasion Modeling
  • Data-driven Marketing
  • Marketing Mix Modeling
  • Convex Optimization and Machine Learning
  • Data Mining at the USPS
  • DSC: Bandit Algorithms for Exploration and Exploitation

Speakers Needed:

  • Cybersecurity
  • Prediction Ethics Panel
  • DSC: VC bounds, Rademacher complexity, and why you should care
  • DSC: What Data Scientists and Statisticians Need to Know about Optimization
  • DSC: SVMs and the Kernel Trick
  • DSC: Bayesian Methods and MCMC
  • Domino, Sense, YHat ScienceBox, DataPad

Is there an event you’d like to see? A topic you’d like to present? Please get in touch via the Meetup site!