housing-library-5500 0.2

Sample code for coding practice

#This Submission consists of soulutions for Tamlep-Assignment-2.1

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

Steps to reproduce:

1. unzip dist/housing_library_5500-0.1-py3-none-any.whl -d wheel_contents
2. cd wheel_contents
3. python3 house_price_prediction/score.py

To activate the environment

conda activate <environment-name>

To export the environment

conda env export > environment.yml

To import the environment

conda env create -f environment.yml

LICENSE

This project is licensed under the MIT license - see the (LICENSE) file for details