Machine learning prediction of the price of used cars

• General Info
• Technologies Used
• Room for Improvement
• Acknowledgements
• Contact

• In this project, I developed several machine learning models to predict the price of used cars.
• The projects contains, feature engineering, data cleaning, data wrangling, exploratory data analysis, visulization and model development.
• Models include: 1) Linear regression, SVM, decision tree, random forest, gradient boosting, Neural Network, etc..
• There are 10 features "trim","isOneOwner","mileage","year","color","displacement","fuel","region","soundSystem","wheelType"
• There is one traget variable "price"

Table of the architecture of the Neural Networks used in this study Table of comparison of the performance of different models

• Python
• SciKit Learn
• Tensorflow
• Pandas
• Matplotlib

• Will implement XGboost later

• Thanks to Dr. Robert McCulloch for fruitful discussions.

Created by Miralireza Nabavi - feel free to contact me!