A series of tutorials and demos on topics of interest to data scientists

The Advanced Topics in Data Science Seminar Series will be held this spring at the eScience Institute. The goal is to provide a closer look at useful techniques in data science in a long-form interactive setting. Over the quarter, we’ll hear from a variety of speakers discussing¬†tools and techniques that go beyond the fundamentals presented in previous courses. The theme this quarter is Bayesian Data Analysis . The seminars are partly interactive, so bring your laptops!

Students may register and receive 1 credit for this course.

Spring 2019 Schedule

Time: Mondays, 3:30 to 5 p.m.

Location: WRF Data Science Studio, sixth floor of the Physics/Astronomy Tower

Date Title Speaker Affiliation
April 15 Hierarchical Bayesian Modeling (slides) Gwen Eadie Postdoctoral Fellow,
UW Astronomy
April 22 An Introduction to Bayesian Belief Networks (slides) Joe Hellerstein Research Scientist, eScience Institute
April 29 Estimating spillovers using imprecisely measured networks Tyler McCormick Associate Professor, Statistics and Sociology
May 6 A Practical Introduction to Bayesian Regression Analysis Woosub Shin Research Scientist, eScience Institute
May 13 Human Mobility: Bayesian and Frequentist Insights from Big Data Adrian Dobra Associate Professor, Statistics
May 20 An Introduction to Variational Inference and its Applications Valentina Staneva Data Scientist, eScience Institute

 

Spring 2018 Schedule

Time: Wednesdays, 10:00 – 11:30 a.m.

Location: WRF Data Science Studio Seminar Room, 6th Floor Physics/Astronomy Tower

Date Title Speaker Affiliation
April 20 (Friday) Tools for Data Cleaning and Munging (files) Ryan Maas Staff scientist, UW eScience
April 25 Tensor Decompositions in Machine Learning (github repo) Valentina Staneva Data Scientist, UW eScience
May 2 Sequential Experimental Design Kevin Jamieson Professor, UW CSE
May 8
Vega-Lite – A Grammar of Interactive Graphics Dominik Moritz Ph.D. Candidate, UW CSE
May 16 Text Classification: From Logistic Regression to Neural Networks (data/slides) Yangfeng Ji Postdoctoral Researcher, UW CSE
May 23 Evaluation Methods for Machine Learning Bernease Herman Data Scientist, UW eScience
May 30 Convex Modeling and Optimization Maryam Fazel Professor, UW EE
June 6 Theoretical Insights on Deep Learning Zaid Harchaoui Professor, UW Statistics