The Random forests machine learning algorithm is a popular ensemble method used by many data scientists to achieve good predictive performance in the classification regime. Fully understanding the nuances of this statistical learning technique is paramount to getting the most out of this algorithm – unfortunately, this means math. The presentation below is from machine learning course CPSC 540 at The University of British Columbia, and takes a detailed view of Random forests by Dr. Nando de Freitas, adjunct professor at UBC Computer Science and a full-time professor at Oxford. If you want to excel at data science you need to master Random forests and this lecture is a great resource for this purpose.
You can download the slides for the Random forest lecture as well as all the other lectures in the class HERE.
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