SE Apartment Project
Turning data into insights and predictors with Machine Learning
The goal of this story and a recap of the last story.
In the previous story, we explored how we could acquire and clean data. While the cleaning and filtering took a lot longer than expected, we ended up with a sparkly clean dataset. To jock your memory, we now have this as our dataset:
SE Apartment Project
Acquiring and cleaning data with Web Scraping in Python
Project Background
Being considered one of the most overpriced housing markets in the world, I figured the apartment market in Stockholm would serve as an interesting case study with a lot of interesting data available. To transform a large portion of data into useful insights that are easy to understand and make a model that predicts the sale price of future apartment listings.
I also decided to make sure to approach this problem in the way a Data Scientist would approach it with some of the head-aches and challenges a real-situation would present. …
Gustaf Halvardsson
Computer Science student at KTH Stockholm. Best described by my curiosity for new areas and technologies. See more of my work at my website: https://halco.se
