housingLibrary-5508 0.1

Sample code for coding practice

#This change is for the Pull request

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.

##Packaging python code and test it using score.py

python -m build (Create a .tgz and .whl files of our project for the packing) twine upload dist.* (Upload our packaging files to the pypi to make it globally accesable to all users) -> Inorder to do upload the files to pypi we need to create an account in the pypi and generate and token.

How to install the package and import the methods

1. Install the package name = housing-library-5512==0.1

pip install housing-library-5512==0.1

2. In code file use these statements to import the required methods.

from src import fetch_housing_data, load_housing_data

Testing with sample code for the package

-> We tested it by running score.py file to test the package