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In this project we tried to solve a $10000 Kaggle competition. Starting with a dataset containing information about buying and selling used cars, we want to determine whether a purchase is a good or a bad purchase through the use of state-of-the-art Machine Learning and AI algorithms.

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carrentals classification clustering decision-trees machine-learning association-rules datamining-algorithms

dont-get-kicked's Introduction

Dont-Get-Kicked

Carvana is an American online start-up that has as core business the retail of used cars. In this business, the ability to predict if a car will be a good or bad purchase brings an essential competitive advantage. This prediction can prevent the risk of unsold cars which causes damages to the prosperity of the company. The aim of this project is to prevent those possible damages analysing the data given by the start-up.

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