On November 15th, my credit risk analytics course will be available as e-Learning. Send me an email at Bart.Baesens@gmail.com Bart Baesens holds a master's degree in Business Engineering (option: Management Informatics) and a PhD in Applied Economic Sciences from KU Leuven University (Belgium). He is currently an associate professor at KU Leuven, and a guest lecturer at the University of Southampton (United Kingdom). He has done extensive research on data mining and its applications.
Anastasia Gnezditskaia is a writer / analyst covering France, Benelux and Morocco. Based in Antwerp, Belgium, she has a background working for trade publications covering markets and their regulation in Washington, D.C., where she lived for 10 years. Following this she managed international development projects in Africa at the World Bank, and worked as a journalist covering Congress, federal government agencies and financial markets, including energy futures.
We use text mining a lot in day-to-day data mining operations. In order to share our knowledge on this, to show that R is an extremely mature platform to do business-oriented text analytics and to give you practical experience with text mining, our course on Text Mining with R is scheduled for the 3rd consecutive year at LStat, the Leuven Statistics Research Center (Belgium) as well as at the Data Science Academy in Brussels. Courses are scheduled 2 times in November 2017 and also in March 2018. This course is a hands-on course covering the use of text mining tools for the purpose of data analysis. It covers basic text handling, natural language engineering and statistical modelling on top of textual data.
It's been almost 15 years since we saw the future of crime prevention in "Minority Report" – but today, we are beginning to see those then fictitious yet fantastical methods of predicting and preventing crime being implemented in various parts of the world. I'll briefly mention three examples below of how analytics is already being used to prevent crime today before going into more detail on a fourth example: using analytics to prevent a criminal from re-offending. In Los Angeles and in England "predictive policing" ("PrePol") has been deployed for over two decades. It has of course evolved over this time. Today PrePol utilises algorithms to identify crime "hot-spots".