DATA DRIVEN MODELING
Mathematical and coding concepts with a focus on Self Organizing Maps
Ubiquitous data streams, being emitted from different aspects of our daily life has opened up new concepts of scientific modeling such as data driven modeling that challenge the classical notions of domain expertise, rule based systems and theory based models of real world phenomena. While we see data streams and Big Data as a new resource for modeling and design, we think its applications become prominent if we look at data via a new set of mathematical and coding skills, which goes beyond geometric thinking.
Toward this goal, in this series of technical seminars we introduce and discuss some of these mathematical concepts (as shown above) in four interlinked categories of Probability Theory and Statistics, Optimization Theories, Linear Algebra and Machine Learning Theories. All the concepts and techniques will be presented using Python programming language and sample data sets, while the objective is to attract architectural researchers to challenge these wild technologies from the perspective of design.
dates: Tuesdays 13:30 – 15:30
introduction: Tuesday, September 22, 2016
place: Chair for CAAD, D-ARCH / ITA / CAAD HIB E 16, unless announced differently
course tutor: Vahid Moosavi