https://github.com/odeyiany2/kagglex-skills-assessment-challenge

This repo contains my python code for predicting the price of a used vehicle for a Kaggle skills assessment challenge.
https://github.com/odeyiany2/kagglex-skills-assessment-challenge

Last synced: 7 days ago
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This repo contains my python code for predicting the price of a used vehicle for a Kaggle skills assessment challenge.

• Host: GitHub
• URL: https://github.com/odeyiany2/kagglex-skills-assessment-challenge
• Owner: Odeyiany2
• Created: 2024-06-01T17:27:50.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-16T22:21:46.000Z (5 months ago)
• Last Synced: 2024-06-16T23:29:16.823Z (5 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 7.88 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
![image](https://github.com/Odeyiany2/KaggleX-Skills-Assessment-Challenge/blob/main/used_car.jpg)

# Used Car Price Prediction using Traditional Machine Learning Models and Neural Networks

This project is for a KaggleX Skills Assessment Challenge. Based on certain features I will be building a model that can predict the price of a used car. 

## Detailed Description of the dataset

* Brand & Model: Identify the brand or company name along with the specific model of each vehicle.

  

* Model Year: Discover the manufacturing year of the vehicles, crucial for assessing depreciation and technology advancements.

  

* Mileage: Obtain the mileage of each vehicle, a key indicator of wear and tear and potential maintenance requirements.

  

* Fuel Type: Learn about the type of fuel the vehicles run on, whether it's gasoline, diesel, electric, or hybrid.

  

* Engine Type: Understand the engine specifications, shedding light on performance and efficiency.

  

* Transmission: Determine the transmission type, whether automatic, manual, or another variant.

  

* Exterior & Interior Colors: Explore the aesthetic aspects of the vehicles, including exterior and interior color options.

  

* Accident History: Discover whether a vehicle has a prior history of accidents or damage, crucial for informed decision-making.

  

* Clean Title: Evaluate the availability of a clean title, which can impact the vehicle's resale value and legal status.

  

* Price: Access the listed prices for each vehicle, aiding in price comparison and budgeting.