Category : Data Science problem - Subject : Predict a House Price , by designing a predictive models using Python
Category : Data Science - Subject : Predict a House Price
This is my first experience in data science area. In Business Intelligence subject in the last course of the Computer Science
degree, I got the oportunity to make my first experience at data science area. I was so lucky so I got Paco Herrera as a profesor
for this subject, so I tried to learn the most of him.
It’s a regression problem. It’s a Kaggle competiton with the following description:
Ask a home buyer to describe their dream house, and they probably won’t begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition’s dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.
With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home
In the project src directory, I put a folder for each effective version (6 versions in total). “effective version: gives higher ranking”