https://github.com/d-kleine/cars_badbuys

Machine Learning workflow for bad buy predictions for used cars
https://github.com/d-kleine/cars_badbuys

classification machine-learning

Last synced: 9 days ago
JSON representation

Machine Learning workflow for bad buy predictions for used cars

• Host: GitHub
• URL: https://github.com/d-kleine/cars_badbuys
• Owner: d-kleine
• Created: 2021-11-22T07:22:54.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2023-07-15T08:43:56.000Z (over 1 year ago)
• Last Synced: 2024-12-06T17:19:12.863Z (about 1 month ago)
• Topics: classification, machine-learning
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/c/DontGetKicked/data
• Size: 8.18 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# ML workflow for bad buy predictions for cars

This repository contains a dataset of cars that have been identified as "bad buys" by the experts in the automobile industry.

The purpose of this dataset is to help people who are looking to buy a used car to avoid making a bad purchase. By analyzing the data, one can identify patterns and trends that could indicate a problematic vehicle. However, it is important to note that this dataset is not exhaustive and should be used in conjunction with other resources when evaluating a used car.

## Data

The data is stored in a CSV file called *bad_buys.csv*. The file contains information about each car, including the make and model, year, mileage, and reason for being identified as a bad buy.