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CAR PRICE PREDICTION

A machine learning program that predicts the price of cars as seen in the dataset given. This program uses a simple ensemble regressor algorithm to predict a reasonable Manufacturer suggested retail price for cars.

Data set and its description

Data Description
Make Company or brand name
Model Car category
Year Production year
Engine fuel type Engine fuel combustion type
Engine HP Horse power capability of the engine
Engine cylinders Number of cylinders
Transmission type Automatic, manual etc
Driven_wheels type of wheel drive
Number of doors Available doors attached to the car
Market_category Targeted audience for the car
Vehicle size dimension of the car
Vehicle style car design appeal
Highway MPG Highway miles travelled
City MPG City miles attainable
Popularity Numeric figure
MSRP Manufacturers' recommended pricing

Dependencies and packages

  1. numpy>=1.20.0,<1.21.0
  2. pandas>=1.3.5,<1.4.0
  3. pydantic>=1.8.1,<1.9.0
  4. scikit-learn>=1.0.2,<1.1.0
  5. strictyaml>=1.3.2,<1.4.0
  6. ruamel.yaml==0.16.12
  7. feature-engine>=1.0.2,<1.1.0
  8. joblib>=1.0.1

Source code link

Source code link: Github link

Release files for car-price-regression-model 3.0.1

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Source distribution (sdist)

Source distribution for car-price-regression-model 3.0.1
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Built distribution (wheel)

Table of built distributions (wheels) for car-price-regression-model 3.0.1
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car_price_regression_model-3.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 506.2 kB

Release files / car-price-regression-model-3.0.1.tar.gz

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3.0.1 This release

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3.0.0

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