Predicting Airbnb prices with machine learning and location data

As part of the IBM Data Science Professional Certificate, we get to have a go at our very own Data Science Capstone, where we get a taste of what is like to solve problems and answer questions like a data scientist. For my assignment, I decided to do yet another project that looks into the relationship between Airbnb prices and its determinants. Yes, there are several very cool ones like Laura Lewis's here. I would not have been able to do mine without reading and understanding hers (and her code), so kudos! However, being that I'm all about transportation research, I added a little touch of geospatial analysis by looking into locational features as possible predictors. This post explains a bit of the project background, data collection, cleaning and pre-processing, modeling, and a quick wrap up. For the complete notebook with all the code, you can check out the repo on my Github.