GitHub / north0n-FI / House-Prices-Advanced-Regression-Techniques
This is my contribution to a competition on kaggle.com, where you have a dataset with 79 explanatory variables describing (almost) every aspect of c. 1500 residential homes in Ames, Iowa. The aim is to predict the final price of each home.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/north0n-FI%2FHouse-Prices-Advanced-Regression-Techniques
PURL: pkg:github/north0n-FI/House-Prices-Advanced-Regression-Techniques
Stars: 1
Forks: 1
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 1.04 MB
Dependencies parsed at: Pending
Created at: about 7 years ago
Updated at: almost 2 years ago
Pushed at: about 7 years ago
Last synced at: almost 2 years ago
Topics: categorical-data, feature-engineering, kaggle-competition, machine-learning, numpy, one-hot-encode, pandas, xgboost