https://github.com/debasish-dutta/car-price-prediction

An end to end ML project based on the kaggle dataset of used car price regression data.
https://github.com/debasish-dutta/car-price-prediction

data-science machine-learning sckit-learn

Last synced: about 2 months ago
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An end to end ML project based on the kaggle dataset of used car price regression data.

• Host: GitHub
• URL: https://github.com/debasish-dutta/car-price-prediction
• Owner: debasish-dutta
• License: mit
• Created: 2020-07-23T05:07:41.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-11-22T15:20:23.000Z (about 2 years ago)
• Last Synced: 2023-03-05T12:26:06.053Z (almost 2 years ago)
• Topics: data-science, machine-learning, sckit-learn
• Language: Jupyter Notebook
• Homepage: https://car-sales-predictor.herokuapp.com/
• Size: 4.05 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# car-price-prediction

## Problem Statement

>Predicting the sale price of used cars

## Data

>The data is downloaded from Kaggle bluebook for used [car dataset](https://www.kaggle.com/nehalbirla/vehicle-dataset-from-cardekho?select=car+data.csv).This dataset contains information about used cars listed on [CarDekho](www.cardekho.com)

## Analysis

I used two models - Random Forrest Regressor and Decision Tree Regressor and these are the evaluations.

- Random Forrest

⋅⋅- MAE: 0.7971604621587255

⋅⋅- MSE: 3.880762431820603

⋅⋅- RMSE: 1.9699650839090024

- Decision Tree

⋅⋅- MAE: 0.9796721311475409

⋅⋅- MSE: 4.938009836065574

⋅⋅- RMSE: 2.2221633234453253