Predicting HDB Prices with MRT distance

This started primarily as a Data Science Project for IBM I am Vitalise Program with a limited scope but grew to include other components.

Please look at other branches for features that have yet to be implemented!

Dataset also available in Kaggle here

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.idea		.idea
.ipynb_checkpoints		.ipynb_checkpoints
.gitattributes		.gitattributes
.gitignore		.gitignore
Decision Tree_pkl.pkl		Decision Tree_pkl.pkl
Extract_MRTCoorAnd_InsertMinDistance.ipynb		Extract_MRTCoorAnd_InsertMinDistance.ipynb
Extract_coordinates_piecemeal.ipynb		Extract_coordinates_piecemeal.ipynb
Extract_missingaddress.ipynb		Extract_missingaddress.ipynb
Extreme Gradient Boosting Machine_pkl.pkl		Extreme Gradient Boosting Machine_pkl.pkl
HDB_models-Copy1.ipynb		HDB_models-Copy1.ipynb
HDB_models.ipynb		HDB_models.ipynb
HDB_predictor.py		HDB_predictor.py
HDBdata with district_coord_dist_full.csv		HDBdata with district_coord_dist_full.csv
IBM-DataScienceProject.ipynb		IBM-DataScienceProject.ipynb
IBM-DataScienceProject2.ipynb		IBM-DataScienceProject2.ipynb
Lasso_pkl.pkl		Lasso_pkl.pkl
Light Gradient Boosting Machine_pkl.pkl		Light Gradient Boosting Machine_pkl.pkl
Linear Regression_pkl.pkl		Linear Regression_pkl.pkl
Minutes Discussion 1 Dec 21.txt		Minutes Discussion 1 Dec 21.txt
README.md		README.md
Ridge_pkl.pkl		Ridge_pkl.pkl
Untitled.ipynb		Untitled.ipynb
Web_scrape_99.co.py		Web_scrape_99.co.py
dnn_model.h5		dnn_model.h5
dnn_model_history_pkl.pkl		dnn_model_history_pkl.pkl
extract_coordinates.py		extract_coordinates.py
resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv		resale-flat-prices-based-on-registration-date-from-jan-2017-onwards.csv
resale-flat-prices.zip		resale-flat-prices.zip
return_min_distance.ipynb		return_min_distance.ipynb

Provide feedback