Introduction to R for Data MiningCourse OverviewR, the premier language for computational statistics has also evolved into powerful and popular tool for data mining. Much of R's core functionality is focused on exploring and understanding data, model design, inference, and visualization and is directly applicable to any data mining effort. But most importantly, the large number of predictive analytics algorithms that have already been implemented in R and the ease with which new algorithms may be developed make R an essential data mining tool. When enhanced with the big data capabilities of Revolution Enterprise 6.0 R becomes the platform of choice for serious data mining projects.In this fast paced course, we focus on data mining as the application area and show how anyone with just a basic knowledge of elementary data mining techniques and some programming skills can become immediately productive in R. The class uses a combination of lecture and labs to instruct students on how to effectively use R for Data Mining. In addition, students will have homework assignments between the sessions to practice the concepts learned. Duration1 dayAudiencePracticing Data Miners new to R R users who want to learn more about the powerful Revolution R EnterpriseData mining students with strong programming skills
PrerequisitesBasic understanding of various Data Mining Techniques.Programming experience in some languageWindows Laptop/Desktop with Revolution R Enterprise installed.Revolution Analytics Training Center Requirements
Course OutlineSection 1Overview of the R language and data mining resources.Using the rattle GUI to get started with Data Mining and RData structures in RR functions and basic statisticsData ExplorationIntroduction to clustering algorithmsIntroduction to classification algorithmsHomework AssignmentsSection 2Introduction to the Caret packageOverview of the RevoScaleR packageReading data to and from .Xdf filesThe RevoScale R Data StepKmeans with RevoScaleRLogistic Regression with RevoScaleRResources for further study About Joseph Rickert, the InstructorJoseph is a Product Marketing Manager at Revolution Analytics with a passion for analyzing data. He has worked a number of successful Silicon Valley start-ups including Sytek, Alantec, Parallan Computer and Scotts-Valley Instruments. He taught statistics briefly at SJSU. He blogs at blog.revolutionanalytics.com.Education: MSc Statistics, Cal State.MA, Humanities, Cal State.BA Mathematics, Franklin & Marshall College.
Areas of Expertise: Big data analytics and visualization
Disclaimer:We have the right to cancel the event for any reason at any time. Revolution Analytics will refund all monies paid for ticket sales in full in the event of a cancellation. We are not responsible for any travel related expenses incurred by attendees for this event.This includes but not limited to transportation, hotel accommodations or any other travel related expenses secured by the attendee, due to a cancellation on our part. Cancellation Policy 30 days from event date - - - Full refund less 10% of the paid ticket price21 days from event date - - - 50% of paid ticket priceWithin 15 days of event date - - - Non refundable Note:Discount offers cannot be combinedA student ID Number is not a proof of full time university enrollment to get the student’s discount. Proof of enrollment in 9 units or more on a current academic registration document will be required to receive the student's discount.The early bird discount will be $100 until one month prior to the starting date of the course.
General Admission 759.95