AkashSDas / predict-prices-of-vehicles

Using data analysis techniques on numerical and categorical data to analysis features of vehicles and creating machine learning model to predict the price of vehicles.

predict-prices-of-vehicles

Here vehicle_prices is used to perform EDA, find features by feature engineering that affects price of vehicles and create a regression model that can predict price of vechicles.

While doing this we'll go through

• Feature engineering on categorical and continuous features
• Dealing with multi-collinearity issues
• Dealing with outliers

Table of contents

• Getting started
• Findings
• Model performance
• License

Getting started

The notebook is available on Kaggle to work in the same environment where this notebook was created i.e. use the same version packages used, etc...

Findings

Correlation matrix

Multi collinearity issue

Price distribution

Correlation matrix for vehicle prices

To see more go to the notebook.

Model performance

Learning curve

RMS error and R2 square metrics

Actual Vs Predicted values

License

APACHE LICENSE, VERSION 2.0