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3 points by isms 3347 days ago | link | parent

Thanks for your interest! The getting-into-ML genre is extremely plentiful out on the internets, so I'll just try to address a couple things I think might be helpful for you on the ground. (I'll go with R because you mentioned it and it's a nice choice to start making the jump from Excel.)

- Breeze through this R intro: http://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-I...

- Work through this longer one, playing along at home in your RStudio -- not trying to memorize, just get comfortable: http://cran.r-project.org/doc/manuals/R-intro.pdf

- Our e-buddy @trevs (Datatau & DrivenData user, and high finisher on our last competition!) put together a great getting started guide for Kaggle's practice challenge: http://trevorstephens.com/post/72916401642/titanic-getting-s...

- (Bonus, not necessary) One book I've heard recommended quite a bit for people making the jump from Excel to R is called "Data Smart: Using Data Science to Transform Information into Insight" - it's by John Foreman, who is a super smart guy and head of data science at Mailchimp. He also writes in an approachable and entertaining style which never hurts.

From there, you should at least know what places you want to focus your efforts and will have a decent beginner knowledge base to start tackling the problem in R with some popular machine learning classifiers.

Good luck, and feel free to be in touch! (isaac or peter at drivendata.org -- hit us up any time)




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