Predictive Analytics World Workshop The Best and the Worst of Predictive Analytics March 2011
|Event Date/Time: Mar 16, 2011||End Date/Time: Mar 16, 2011|
Common Data Mining Mistakes
Instructor: John F. Elder IV, Chief Scientist, Elder Research, Inc.
Web Site: http://www.predictiveanalyticsworld.com/sanfrancisco/2011/predictive_modeling_methods.php
Date: Wednesday March 16, 2011 in San Francisco
Interested in the true nuts and bolts. A free copy of John Elder's book Statistical Analysis and Data Mining Applications is included. Knowledge Level: Familiar with the basics of predictive modeling. Attendees will receive an electronic copy of the course notes via USB drive.
Predictive analytics has proven capable of enormous returns across industries â€“ but, with so many core methods for predictive modeling, there are some tough questions that need answering: How do you pick the right one to deliver the greatest impact for your business, as applied over your data? What are the best practices along the way? And how do you avoid the most treacherous pitfalls?
This one-day session surveys standard and advanced methods for predictive modeling.
Dr. Elder will describe the key inner workings of leading algorithms, demonstrate their performance with business case studies, compare their merits, and show you how to pick the method and tool best suited to each predictive analytics project. Methods covered include classical regression, decision trees, neural networks, ensemble methods, uplift modeling and more.
* Workshop starts at 9.00am
* First AM Break from 10:00 - 10:15
* Second AM Break from 11:15 - 11:30
* Lunch from 12:30 - 1:15pm
* First PM Break: 2:00 - 2:15
* Second PM Break: 3:15 - 3:30
* Workshops ends at 4:30
Attendees receive a free copy of John Elder's book Statistical Analysis and Data Mining Applications, an electronic copy of the course notes via USB drive, and an official certificate of completion at the conclusion of the workshop.
For more information: http://www.predictiveanalyticsworld.com/sanfrancisco/2011/predictive_modeling_methods.php
For inquiries e-mail firstname.lastname@example.org or call (717) 798-3495.