ammartin8 / housing_price_prediction

Project Title: Housing Price Prediction

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Author: Amah Martin Created: 04-30-2022

Table of Contents

• Project Summary
• Technical Summary
• Features
• Milestones
• Requirements to Run the Application

Project Summary

This is a data science project reviewing housing prices developing a model in order to predict the final sales price of homes based upon 79 explanatory features describing residental homes in Ames, Iowa.

Reference: House Prices - Advanced Regression Techniques

Technical Summary

The following main technologies are used to analyze the data:

Tools

• Python 3.8

Python Libraries

• pandas
• numpy
• matplotlib.pyplot
• seaborn

Features

Core Features will include the following:

1. A jupyter notebook containing an overview of the exploratory data analysis phase of the project
2. A jupyter notebook containing an overview of the feature engineering phase of the project
3. A jupyter notebook describing the process of feature selection and model development and deployment including final csv submission file.

Milestones

1. Exploratory Data Analysis ✔
2. Feature Engineering
3. Feature Selection
4. Model Building
5. Model Deployment

Requirements to Run Application

• Ensure you have Python 3 program downloaded first as well listed python libraries
• Make a pull request or download the files from the GitHub repository
• In terminal navigate to root folder of project and you will be able to review the jupyter notebooks found in the root folder