Published on: Mar 4, 2016
Transcripts - Pricing information
In Production: The 2008 2-Day Course on DVD
“Tools for Discovering Patterns in Data: A Survey of Modern Data Mining Algorithms”
Could not make it to this year’s conference? Would like to save money by still hearing
the conference without attending? Then place your order for a copy of the DVD for the
2008 2-Day Conference. The DVD is currently being worked on, so let us know if you
are interested by sending an email to David Newman, firstname.lastname@example.org. If
you would like subtitles in another language, please include that request in the email.
Find the useful information hidden in your data! This course surveys computer-intensive
methods for inductive classification and estimation, drawn from Statistics, Machine
Learning, and Data Mining. Dr. Elder will describe the key inner workings of leading
algorithms, compare their merits, and (briefly) demonstrate their relative effectiveness on
practical applications. We'll first 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),
Resampling, 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.
John Elder is Chief Scientist of Elder Research Inc., a Data Mining consulting firm in
Charlottesville, Virginia. He has over twenty years of experience developing and
applying adaptive, data-driven techniques to practical problems - at an engineering
consulting firm, an investment management company, Rice University, and the
University of Virginia. Dr. Elder has written and spoken widely on pattern discovery
topics, is active on statistical and engineering journals and boards, and has authored some
influential data mining tools. His practical experience with commercial applications -
including credit scoring, direct marketing, sales forecasting, market timing, and fraud
detection - help illustrate the course concepts.
Those from industry and academia who work with data and wish to understand recent
developments in pattern discovery, data mining, and inductive modeling. At the
conclusion of this course, one should be able to discern the basic strengths of competing
methods and select the appropriate tools for one's applications. Participants should have
prior working experience with computers and interest in applied statistical techniques. (It
helps, as well, to have a motivating application you wish to solve.)
Comments from previous attendees:
• "[Dr. Elder] provided examples shedding light on complex concepts. He gave the
big picture all along the way."
• "Gave real practical insights from a practitioner's point of view."
• "Finally someone told me how things are done, not just how great Data Mining
• "Most valuable, were the insights into the essence of various methods, their
relative strengths and weaknesses, and the important open research areas."
• "Very interesting, knowledgeable, and entertaining approach."