Title: Machine Learning Techniques and Selected Applications for Big Data
Lecturer: Stan Matwin (Dalhousie University, Canada)
Period: February 22, 25, 29 - March 3, 7, 10, 14, 17, 21, 24 2016
Timetable: Mon. 11:00-13:00 Thu. 14:00-16:00
Place: Department of Computer Science Sala “seminari ovest"
Stan Matwin is a Professor and Canada Research Chair in the Faculty of Computer Science at Dalhousie University, Canada, where he directs the Institute for Big Data Analytics. He is also a Professor at the Institute of Computer Science, Polish Academy of Sciences. His research interests are in text analytics, data mining, as well as in data privacy. Author and co-author of more than 250 research papers and articles, Stan is a former President of the Canadian Artificial Intelligence Society, a member of the Scientific Council of the Polish Artificial Intelligence Society, and a member of Association Francaise pour l’Intelligence Artificielle.
1. Intro (def, challenges, nosql etc.) 2h
2. Linear methods 2h
3. Bayesian Methods 3h
4. Stream Data Processing: VFDTs 2h
5. Vizualization: basics, examples 3h
6. Privacy for Big Data: data summaries (scripts, Bloom filters), ABAC approaches (Acumulo) 3h
7. Applications: Oceans 2h
8. Applications: Big Data in the Public Sector 2h
9. Data tagging challenges for Big Data: crowdsourcing, reCaptcha 1h