Car Price Predictor: Unlocking Insights For Used Car Buyers And Seller

• Author(s):

  Mr. R. Mr.R.Saravanan | Parvadhakrishnan V

• Keywords:

  Machine Learning, Used Car Price Prediction, Feature Engineering, Regression Models, Data Preprocessing

• Abstract:

  The Automotive Industry Is Witnessing A Paradigm Shift With The Increasing Demand For Used Cars. As Consumers Explore Cost-effective And Sustainable Transportation Options, The Valuation Of Used Cars Becomes A Critical Aspect Of The Buying And Selling Process. This Research Presents A Comprehensive Study On Predicting Used Car Prices Through The Application Of Machine Learning Algorithms. Our Approach Involves Collecting And Analyzing Various Parameters Such As Mileage And Other Relevant Features That Influence The Pricing Dynamics Of Used Cars. Leveraging A Diverse Dataset Encompassing A Wide Range Of Cars, Our Machine Learning Models Aim To Learn The Intricate Relationships Between These Parameters And The Market Value Of Used Cars. Feature Engineering Techniques Are Applied To Enhance The Model's Ability To Capture Nuanced Patterns Within The Data. The Dataset Is Meticulously Preprocessed To Handle Outliers, Missing Values, And Categorical Variables, Ensuring The Robustness Of The Predictive Models. The Developed Predictive Models, Empowered By Machine Learning, Serve As Valuable Tools For Both Buyers And Sellers In The Used Car Market. By Providing Accurate And Data-driven Estimates Of Car Prices, Our Approach Contributes To Transparency, Efficiency, And Informed Decision-making In The Dynamic Landscape Of Used Car Transactions.

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Other Details

• Paper id:

  IJSARTV11I5103615

• Published in:

  Volume: 11 Issue: 5 May 2025

• Publication Date:

  2025-05-20

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