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STEERS4U – Car Price Estimator

EasyChair Preprint no. 9266

5 pagesDate: November 7, 2022


Buying a car has been a dream for many middle class people. Some of them may not afford a brand new car. Some of them may need a luxury car for a cheaper price [5]. That’s where the second hand car market comes into the play. Many of the customers are very much confused about the genuine pricing of the cars in the second hand market. We are here to deliver a brand new Web- Application which predicts the price of the desired car the customer wishes to buy. In this project we are planning to include almost all the top manufacturers in the market and all the models present in the second hand market. The primary focus of this project is developing a Machine Learning model that can accurately predict the price of a used car based on its purchase history and kms completed. We have used various datasets to train a Machine Learning model and have deployed it as a Web-Application with seamless User-Interface and User-Experience.

Keyphrases: Bootstrap, Flask, NumPy, Pandas, SciPy, Sklearn, user experience, user interface

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {R Deeptha and Keshav S Vardhan and Sachin N Srinivas and E Balaji},
  title = {STEERS4U – Car Price Estimator},
  howpublished = {EasyChair Preprint no. 9266},

  year = {EasyChair, 2022}}
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