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Prediction of Price of Pre-owned cars with the help of car model, how long distance it have covered, whether it is in running condition or not, car's model, fuel_type etc

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Predicting_Price_of_Pre_Owned_Cars

Prediction of Price of Pre-owned cars with the help of car model, how long distance it have covered, whether it is in running condition or not, car's model, fuel_type etc

Problem Statement:

Storm Motors is an e-commerce company who act as mediators between parties interested in selling and buying pre-owned cars,

For the year 2015-2016, they have recorded data about the seller and car including- Specification details Condition of car Seller details Web advertisement details Make and model information Price

Storm Motors wishes to devlope an algorithm to predict the price of the cars based on various attribute associated with the car.

Variable Description

dateCrawled- date when the ad first crawled, all field values are taken from this date

name- string consisting of car's name, brand, model etc.

seller- nature of seller

offerType- whether the car is on offer or not

price- price on the ad to sell the car

abtest- two version of ad

vehicleType- type of cars

yearOfRegistration- year in which car was registered

gearbox- type of gearbox

powerPS- power of the car (in HP)

model- model type of cars

Kilometer- No. of kilometer the car have travelled

monthOfRegistration- month of registartion

fuelType- type of fuel car use

brand- make of car

notRepairedDamaged- Status of repairing of daamges if yes damages have not been rectified; if no damage were taken care of

dateCreated- date at which the ad at storm motor was created

postalCode- postal code of seller

lastSeen- when the crawler saw this ad last online

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Prediction of Price of Pre-owned cars with the help of car model, how long distance it have covered, whether it is in running condition or not, car's model, fuel_type etc

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