Date(s) - 11/09/2018 - 11/10/2018
9:00 am - 5:00 pm
The first day starts with an overview of machine learning and continues with an introduction to the basic techniques. Topics for day 1 include cross-validation, multiple regression, and basic variable selection methods, as well as an overview of the R statistical framework. The second day focuses on advanced variable selection methods for regression analysis. Topics include multivariate adaptive regression splines, lasso regression, classification and regression trees, bagging, and random forests. Throughout the course, participants gain experience with these methods through hands-on exercises.
If you have a desire to learn how to effectively explore your data and have a strong statistical background in regression, this course is for you. You should have a good working knowledge of the principles and practice of multiple regression.
The course does have a fee of $995, which includes all the course material. There is a early registration fee available until October 9. CLICK HERE to register for the course.
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