Metadata-Version: 2.4
Name: Shankar_Python_package
Version: 0.1.0
Summary: Python packaging for MLE Training
Author-email: Shankar <gowri.gopalakris@tigeranalytics.com>
License: MIT
Project-URL: Homepage, https://github.com/Shankar-95/mle-training/Python_package
Description-Content-Type: text/markdown
Requires-Dist: requests
Requires-Dist: numpy

# Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data. 

The following techniques have been used: 

 - Linear regression
 - Decision Tree
 - Random Forest

## Steps performed
 - We prepare and clean the data. We check and impute for missing values.
 - Features are generated and the variables are checked for correlation.
 - Multiple sampling techinuqies are evaluated. The data set is split into train and test.
 - All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

## To excute the script
python < scriptname.py >
