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Data Mining Software Workshops For Today's Data Scientists

Salford Systems Hosts Data Mining Software Computer Training Workshops At The Joint Statistical Meetings


News provided by

Salford Systems

Aug 02, 2013, 10:00 ET

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MONTREAL, Aug. 2, 2013 /PRNewswire-iReach/ -- The recent launch of the Salford Predictive Modeler software suite v7.0, the latest version of Salford Systems' data mining software package, spurred enormous interest in the data science community, especially after its showcase webinar series: "The Evolution of Regression modeling." The series' instructors, Salford Systems' CEO and Founder Dr. Dan Steinberg and Senior Scientist Mikhail Golovnya, will continue this showcase of the software's forefront predictive methodology at the Joint Statistical Meetings in Montreal on Wednesday, Aug. 7, 2013.

For the last decade Salford Systems has hosted computer training workshops at JSM to educate the leading statisticians, analysts, data scientists, and researchers on its flagship products CART® decision trees, MARS® nonlinear regression, TreeNet® stochastic gradient boosting, and Random Forests®. In conjunction with the software suite's new model compression techniques and hybrid modeling capabilities, Salford Systems will present yet another new algorithm that has been added to the Salford toolkit, Generalized PathSeeker (GPS).  This technology includes methods like LASSO, Ridge, and regularized regression.

"Our series of short courses provides an ideal way to quickly upgrade your data mining, machine learning, and modern analytics skill," said Steinberg. "Methods covered include topics relevant to perfecting predictive models and learning machine technology relevant to Big Data."

Join Steinberg and Golovnya at Le Westin Montreal - San Antoine Room for four computer training workshops. The schedule is as follows:

8:00am - 9:45am: Introduction to Data Mining with CART Classification and Regression Trees
(Session ID 209201)

10:00am - 11:45am: Data Mining with TreeNet (Stochastic Gradient Boosting) and Random Forests
(Session ID 209202)

1:00pm - 2:45pm: Introduction to Modern Regression Analysis Techniques: Linear, Logistic, Nonlinear, Regularized, GPS (Generalized Path Seeker), Lars, Lasso, Elastic Net, and MARS (Multivariate Adaptive Regression Splines)
(Session ID 209203)

3:00pm - 4:45pm: Applied Data Mining Analysis: A Step-by-Step Introduction Using Real-World Data Sets
(Session ID 209204)

Salford Systems will also host an exhibit booth at JSM. To schedule a time to meet with Dr. Steinberg, please contact Lisa Solomon at [email protected] or by phone at 619-543-8880.

About JSM
The Joint Statistical Meetings is the largest gathering of statisticians held in North America. It is held jointly with the American Statistical Association, the International Biometric Society, the Institute of Mathematical Statistics, the Statistical Society of Canada, the International Chinese Statistical Association, and the International Indian Statistical Association. Attended by more than 6,000 people, meeting activities include oral presentations, panel sessions, poster presentations, continuing education courses, an exhibit hall, networking and more. For more information about JSM 2013, visit http://www.amstat.org/meetings/jsm/2013/.

About Salford Systems
Founded in 1983, Salford Systems specializes in providing new-generation data mining and predictive modeling software and consulting services for industries such as banking, insurance, healthcare, pharmaceutical, telecommunications, transportation, manufacturing, retail and catalog sales, and education. The company's CART, MARS, TreeNet and Random Forests data mining software is currently installed in over 3,500 sites worldwide, including 300 major universities. Salford Systems is headquartered in San Diego, CA. For more information, visit http://www.salford-systems.com or telephone (619) 543-8880.

Media Contact: Heather Hinman, Salford Systems, 619-543-8880, [email protected]

News distributed by PR Newswire iReach: https://ireach.prnewswire.com

SOURCE Salford Systems

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