AutoValuate is a cutting-edge solution designed to revolutionize the way used car prices are determined. By leveraging advanced machine learning techniques, our project aims to classify used cars into 'High' or 'Low' price categories, enabling businesses and individuals to make informed decisions in the used car market.

In the quaint town of Radiator Springs, Mator dreams of starting a used car resale business but is baffled by the intricacies of pricing. Enter AutoValuate: a tool crafted by some of the brightest minds from Seattle University's Albers School of Business and Economics, aimed at demystifying car pricing for Mator and others alike.

With around 30,000 entries and over 60 features, our dataset presents a unique challenge - it lacks exact pricing information. Instead, we adopt a binary classification approach, marking a significant step towards solving the puzzle of car valuation without direct price data.

• Data Preparation: Dive deep into data cleansing and preparation to ensure quality inputs for our models.
• Exploratory Analysis: Identify key features that influence used car prices.
• Model Development: Train and validate multiple machine learning models to find the best predictor for our binary classification problem.
• Prediction and Application: Utilize our best model to forecast price categories for a fresh set of used cars.