Passenger Satisfaction Prediction End-to-End ML

Description

Built and deployed a machine learning pipeline to predict passenger satisfaction using multiple ML models, including feature engineering and model evaluation.

Tools

Python, Pandas, Numpy, Scikit-learn, Flask

Highlights

Automated pipeline for preprocessing and training.

Compared multiple algorithms (Random Forest, XGBoost, etc.).

Final model deployed via API.