Whose Scat Is That? An 'Easily Digestible' Intro to Predictive Modeling & caret!

Max Kuhn, author of the popular caret package (training Regression & Classification models), and Director of Non-Clinical Statistics at Pfizer Global R&D in Connecticut, US will be running a special tutorial especially for R-Ladies whilst visiting the UK for a conference!

This is a unique opportunity, and will be of particular value to Intermediate R users+ who want to learn about predictive modeling in R in general, and using the caret package specifically. The hands-on tutorial will assume a general level of working ability with R, so please be aware there is a knowledge/skill/interest pre-requisite for gaining maximum benefit from this session!

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REQUIRED PACKAGES: there will be no public WiFi, therefore you MUST install the required packages beforehand. You can run this code:

pkgs <- c("caret", "nnet", "glmnet", "RANN", "ipred", "rpart")

for(i in pkgs)

install.packages(i, dependencies = c("Depends", "Imports", "Suggests"))

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REGISTER ON EVENTBRITE TO ATTEND!!!!

https://www.eventbrite.com/e/r-ladies-oct-workshop-intro-to-predictive-modeling-the-caret-package-tickets-27656253599?aff=es2

You MUST have your free Eventbrite ticket for entry!! Meetup RSVP will NOT give you entry to this event.

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PLEASE ASSEMBLE BY 6.15pm on Norfolk Place as indicated by the yellow arrow - there will be one-time only batch entry into the building, so you MUST be present at 6.15pm or you won't be let in and will miss the workshop!!

http://photos4.meetupstatic.com/photos/event/6/b/a/2/600_454587554.jpeg

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As always, all are welcome to attend as learners regardless of gender, R proficiency, or other attribute - we aim to be a fully inclusive, diverse user group, whilst maintaining our commitment to promoting R amongst women.

Code of Conduct: anyone who violates or has previously violated this community's Code of Conduct will be refused entry, expelled, and/or any other action deemed appropriate by the Organiser, regardless of event registration, meetup membership or other condition.