Celestial Object Classification with ML

This presentation explores celestial classification using Machine Learning techniques, leveraging the SDSS dataset. Starting with an overview of the project, it delves into the challenges and motivations in astronomy, highlights data exploration and visualization findings, and explains the methodology involving Random Forest, SMOTE, and SHAP tools for model performance and interpretability. Results showcase optimized classification accuracy and detailed evaluations, followed by deployment...