Car Price Prediction Web Application
Developed a machine learning application that predicts car prices based on vehicle features such as brand, model, year, fuel type, transmission, and mileage.
Key Responsibilities:
Collected and prepared car price data for analysis.
Performed data cleaning and preprocessing.
Conducted Exploratory Data Analysis (EDA) to identify patterns and relationships.
Built and trained a machine learning model for price prediction.
Evaluated model performance using appropriate metrics.
Developed an interactive web interface using Streamlit.
Enabled users to enter car details and receive instant price predictions.
Technologies Used:
Python
Pandas
NumPy
Scikit-learn
Matplotlib
Seaborn
Streamlit
