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 - [Predicting Forest Fire Causes](https://github.com/mkfrancsis/Thinkful-Supervised-Learning-Capstone) by Matt Francsis.
 Human-caused fires account for between 43 and 59% of all wildfires in the western US. While wildfires can be beneficial to the ecosystem, they also pose serious threats to lives, property, and infrastructure. Predicting the cause of forest fires can assist investigators bring arsonists to justice and act as a catalyst for fire abatement strategies. This talk will discuss supervised learning modeling techniques for this large, imbalanced, multi-class, problem.
 
+- [Predicting prices for AirBnB listings in Berlin](https://github.com/RobKnop/ThinkfulDataScienceBootcamp/blob/master/Main/3.7_CapstonePresentation.pdf) by Robert Knop. As a host you would like to know how much money you should take per night. This project shows different preprocessing approaches (MinMax, box-cox) and models (RidgeRegression, KNN, Random Forest, Gradient Boosting, SVM). See the [notebook](https://github.com/RobKnop/ThinkfulDataScienceBootcamp/blob/master/Main/3.7_CapstoneBerlinAirBnBListings.ipynb). 
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 ## Unsupervised learning report
 
 - [Math lectures Part 1](https://github.com/ExtraLime/math-lectures) Combine NLP with supervised and unsupervised learning to classify math lectures. By William Morgan.