Vehicle-Price-Prediction

Purpose:

Creating machine learning models to predict vehicle price.

Process

1. Store data at postgeSQL
2. Build pipelines and link the dataset to Jupyter Notebook
3. Perform ETL and use matplotib to analyze the dataset
4. Feed to various machine learning models: Linear Regression, Random Forest Regressor, XGBoost Regressor

Data analysis for market

The link to the Tableau Public dashboard can be found here.