Classical statistical techniques, both linear and nonparametric, will be reviewed and then the ways in which these basic tools are modified and combined into powerful modern methods will be outlined. The course emphasizes practical advice and focuses on the essential techniques of Resampling, Visualization, and Ensembles. Actual scientific and business examples will illustrate proven techniques employed by expert analysts. Along the way, relative strengths and distinctive properties of the leading commercial software products for Data Mining will be discussed.
This intensive short course provides a broad overview, drawing connections between major developments in the diverse fields that contribute to Predictive Analytics, including cutting-edge ways to mine text and graphical networks. Previous participants have found this "big picture" to be very useful for identifying techniques to use immediately, as well as approaches worthy of further exploration, for research or practical problem-solving.
Those who work with data and wish to understand and use recent developments in predictive analytics. At the conclusion of this course, you should be able to discern the basic strengths of competing methods and select the appropriate tools for your applications.
$1000 per person-Includes a complimentary copy of the “Handbook of Statistical Analysis and Data Mining”
- "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 is."
- "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."