Kaggle House Prices Competition

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Table of Contents

• About the Project
• Prerequisites
• Presentation
• Technologies Used
• The Team

About the Project

• Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.
• With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

Prerequisites

• Python version 3.0 and above

$python --version
Python 3.7.4

• Jupyter notebook

Presentation

Technologies Used

• Numpy - Numerical Computing Tool
• Pandas - Data Analysis and Manipulation Tool
• Scikit-learn - Machine Learning library
• Seaborn - Data Visualization

The Team

Ryan Park

Sita Thomas

Lucas Kim