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Machine Learning with R
November 16, 2017 @ 6:00 pm - 9:00 pm UTC+0
UPDATES: Materials are now up on my git repo https://github.com/ksasso/MLmodels_inR_GDG2017
git clone to make a copy OR download a zip of all the files by navigating to the green “Clone or Download” button in the right hand corner and selecting “Download Zip”
THERE WILL BE PIZZA thanks to the Columbus Collaboratory!
At this meet up Katie Sasso will provide a crash course on implementing some of the most popular machine learning algorithms and techniques. Specific topics may include Decision Trees, ensemble methods (gradient boosting vs. bagging/bootstrapping), Random Forests, and Neural Networks. Attendees can expect a very high-level overview of techniques, a review of the circumstances under which they are and aren’t appropriate for use, and a brief crash course on how to implement each using R!
This meetup is not appropriate for very beginner level R users, we expect you to be familiar with fundamental R objects and functions.
Parking: Park in any spot marked “Reserved for the Columbus Collaboratory”. There should be more than enough available- all are free. If you find that these spots are filled – park anywhere in surrounding lots and Katie will give you a day pass for your dashboard.
Call Katie if any issues finding it [masked]).
Directions and map also available here: