Workshop Overview
You will be able to find the useful information hidden in your data, find patterns and exploit them for competitive advantage. This Course explains computer-intensive methods for classification and estimation, drawn from Statistics, Machine Learning, and Data Mining. The course facilitator will describe the key inner workings of leading algorithms, compare their merits, and demonstrate their relative effectiveness on practical applications. The Course will firstly review classical statistical techniques, both linear and nonparametric, then outline the ways in which these basic tools are modified and combined into more modern methods. The Course pays particular attention to four powerful topics: modern algorithms (such as Neural Networks and Decision Trees), Re-sampling, Visualization, and Ensembles. Actual scientific and business examples illustrate practical techniques employed by expert analysts. Along the way, major relative strengths and distinctive properties of the leading commercial software products for Data Mining will be discussed, providing deliverables across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, high technology, insurance, publishing, retail and academia.
Workshop Facilitator Profile
The Course Facilitator leads the world’s leading firm for consulting in Data Mining and Predictive Analytics based in Virginia and Washington, DC, USA. John holds a BS and MEE in Electrical Engineering from Rice University, and a PhD in Systems Engineering from the University of Virginia, where he’s an Adjunct Professor teaching Optimization or Data Mining at the Department of Systems and Information Engineering. The Facilitator has authored innovative data mining tools, is a frequent keynote speaker, and most recently was Chair of the 2009 ACM SIGKDD Knowledge Discovery & Data Mining Conference in Paris. He was honored to serve 5 years on a Panel appointed by the U.S. President to guide Technology for National Security. His book on practical data mining, ‘Handbook of Statistical Analysis and Data Mining Applications’ was published only recently in May 2009 to wide acclaim.
Past Training and Consulting Clients include:
- Universities: MIT Sloan Business School, Harvard School of Public Medicine, University of Virginia (McIntire School of Commerce, Darden Business School, Systems and Information Engineering, Statistics), Fairfield University School of Business, Rice University (Computational and Applied Mathematics, Statistics, Continuing Education), George Mason Applied Engineering & Statistics, Baylor Medical School Urology, Virginia Polytechnic Institute Aerospace and Oceans Engineering, U. of Alabama at Huntsville Computer Science.
- Corporations: AT&T Bell Labs, Capital One, HSBC, Fannie Mae, Bell Atlantic, The Nature Conservatory, Continental Airlines, Pitney Bowes, MetLife, Nationwide, Pharmacia & Upjohn, Becton-Dickinson, American Management Systems, Citibank (England), Daimler-Benz (Germany), Insurance Services Office, Lindner Funds, Rio Grande Medical Technologies, Electronic Warfare Associates, Peoples Bank, Federal Data Corporation, Glaxo-Smith-Kline, Salford Systems, Martin Marietta.
- Government Agencies: National Security Agency, National Science Foundation, IRS, National Academy of Sciences, Social Security Administration, Defense Finance and Accounting Agency, U.S. Naval Weapons Center.
- Professional Associations: Society for Industrial and Applied Mathematics, Biopharmaceutical Society, American Statistical Association, Knowledge Discovery & Data Mining (KDD), Institute of Electrical and Electronics Engineers (IEEE), Institute for Professional Education, Interface Foundation of North America, IEEE Systems, Man & Cybernetics Society; American Marketing Association, Pharmaceutical Management Science Association, International Communications Forecasting, Applied Statistics.
- Conferences: ACM Knowledge Discovery and Data Mining, Predictive Analytics World, SAS Data Mining Conference, Annual Predictive Modeling for Underwriting Conference, International Business Rules Forum, Insurance Data Management Association Conference, Salford Systems Data Mining Conference, IEEE International Conference on Data Mining , SIAM International Conference on Data Mining, American Marketing Association - Advanced Research and Technical Forum.
Who Should Attend
Data Mining | Data Warehousing/Database - Practitioners/Modelers/Extractors | Customer/Data Analytics | CRM/Marketing Research | Business Analysts/Intelligence | Decision Support/Management | Portfolio/Project/Campaign Management Unit | Academics - Statisticians/Computer Science
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Media Partners
Sponsors Opportunities
To discuss more on the various sponsorship packages available, please contact +65 6825 9579 or email us at sponsor@unistrategic.com.
Delegates Opportunities
To find out more about the program, please contact +65 6825 9579 or email us at registration@unistrategic.com
Be our Speaker
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Venue & Accomodation
Crowne Plaza Mutiara Hotel,
Kuala Lumpur Malaysia
Jalan Sultan Ismail, 50250 Kuala Lumpur, Malaysia
Contact: Gerald Goh (Crowne Meetings Planner)
Tel. No: +603 2148 2322
Fax No: +603 2146 3881
Email: gerald.goh@crowneplazamutiarakl.com
Website: www.crowneplaza.com/kualalumpur
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