Data Science Meetup on Random Forests for Remote Sensing

[Steven Filippelli]

Hi all,

I'm giving a brief (~1 hr) intro to Random Forests for the Fort Collins Data Science Meetup group on Tuesday March 5th at Front Range Community College Mt Antero Building room 207. After talking about the basics and why this model is so great, I'll be doing some demos on how to apply the model for land cover classification and (maybe) regression of tree cover using satellite imagery. 

I'm hoping to run the workshop with a Google Colaboratry notebook so it'll be easy for everyone to get setup and started. If you don't have a laptop you can still follow along and work with the script later at home. Let me know if you're interested but can't make it and I can send you a link to the script. If there's enough interest I could redo the workshop somewhere on campus.

Details:

Random Forests for Remote Sensing

Random Forest is a versatile model that is quick and easy to implement, robust to overfitting, and produces reasonable accuracy with minimal tuning. We'll look at the basics of how this model works and some of the beneficial attributes which make it useful for classification and regression problems as well as variable selection. Then we'll walk through an application of classification by mapping land cover type from satellite imagery, and (time willing) we'll also go through a regression example by mapping percent tree cover. Through these examples we'll see the influence of hyperparameters on model accuracy and processing time, the effect of multi-collinearity on variable importance, and tools for drawing inference such as partial dependence plots.

[Steven Filippelli]

Sorry, I forgot to include that it will be from 6:30 pm till about 8 pm on Tuesday March 5th.

[Ned Molder]

Thanks for sharing Steve, sounds awesome!