Ricardo Ñanculef is Assistant Professor of the Department of Informatics at the Federico Santa Maria Technical University (Chile). He received the Ph.D from the same university in December 2011 with a dissertation on Support Vector Machines. During 2012-2013 he was a Visiting Researcher at the Intelligent Systems Lab of the Bristol University (UK), doing research on text and data stream mining. Previously, between 2009-2010 he had an internship period at the University of Bologna as an exchange student, preparing this Ph.D project under the supervision of Prof. Claudio Sartori. Among others, he currently keeps scientific collaborations with researchers from the University of Bristol (UK), University of Barcelona (Spain) and RIKEN Brain Science Institute Lab for Neural Circuits and Behavior (Japan). He serves regularly on the program committees for several international conferences on machine learning and pattern recognition.
This course provides a brief introduction to machine learning for statistical pattern recognition. Topics include: a background on decision and supervised learning theory, classic generative and discriminative models, support vector machines, neural networks, ensemble methods and model selection practices. The course also puts emphasis on the application of these models and techniques to practical problems drawing on (Python) code examples and exercises.