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EVENT DETAILS |
This class will get attendees up to speed on predictive modeling using the R programming language. The goal of the course is to understand the general predictive modeling process and how it can be implemented in R. A selection of important models (e.g. tree-based models, support vector machines) will be described in an intuitive manner to illustrate the process of training and evaluating models.
Learn with our NYC Data Science Program (Our Company has worked with over 40 firms in NYC alone, ranging from corporate to individual training). We also conduct a 12-Week Data Science Bootcamp, where classes can be taken during the day, nights, or weekends. We offer flexibility to work with your schedule to learn.
Our next 12-Week Data Science Bootcamp starts in February. (Deadline to apply is Jan 15th, all decisions will be made by Jan 16th.)
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Max Kuhn, Director is Nonclinical Statistics of Pfizer and also the author of
Applied Predictive Modeling
He will join us and share his experience with Data Mining with R.
Max is a nonclinical statistician who has been applying predictive models in the diagnostic and pharmaceutical industries for over 15 years. He is the author and maintainer for a number of predictive modeling packages, including: caret, C50, Cubist and AppliedPredictiveModeling. He blogs about the practice of modeling on his website at ttp://appliedpredictivemodeling.com/blog
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