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Bay Area R User Group 2009 Kickoff Video

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Ron Fredericks writes: In February I attended the Bay Area R User Group meeting recently held at Predictive Analytics World 2009. Michael E. Driscoll, one of the two kickoff meeting co-chairs, was gracious enough to let LectureMaker capture the video for the event as a technical marketing “lighthouse” project.

Today I am happy to present this video to my readers.

If you manage the marketing, feature roll-out, or web site design, for a social network or professional ecosystem, then you need the techniques presented in this video.

Watch this video to learn about:

The open-source analytics programming language called R
How Google and Facebook approach analytics to predict their web user community’s behavior
Where to download R and get enterprise level support
How the meeting co-chairs use R

 

Panel of four recognized R users from industry:

  • Bo Cowgill, Google
  • Itamar Rosenn, Facebook
  • David Smith, Revolution Computing
  • Jim Porzak, The Generations Network

Moderator and co-chair of Bay Area R User Group:

  • Michael E. Driscoll, Dataspora LLC


A live R demo
The co-chairs, Michael and Jim, presented a great overview of the R language. Here at LectureMaker, source code highlighting is supported with automatic links back to language documentation for 132 languages plus my own R highlighter.

For example, here is a short R program:

Code (r)
  1. x <- rnorm(100)            # 100 random numbers from a normal(0,1) distribution
  2. y <- exp(x) + rnorm(100)   # an exponential function with error
  3. result <- lm(y ~ x)        # regress x on y and store the results
  4. summary(result)            # print the regression results
  5. plot(x,y)                  # pretty obvious what this does
  6. abline(result)             # add the regression line to the plot
  7. lines(lowess(x,y), col=2)  # add a nonparametric regression line (a smoother)
  8. hist(result$residuals)     # histogram of the residuals from the regression
  9. # source code reference: http://bayes.math.montana.edu/Rweb/Rweb.general.html

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