A pseudo-spectral collocation based multi-phase Optimal control problem solver

The Falcon 9 Landing Success Prediction project predicts Falcon 9 first-stage landings using machine learning models like Logistic Regression, Random Forest, Gradient Boosting, and Neural Networks. Key features include payload mass, orbit type, and booster reuse. Data is balanced with SMOTE for better accuracy.

This project aims to predict the success of SpaceX Falcon 9 first stage landings using data analysis and machine learning techniques.