Mushroom Classification Project

Developed a machine learning model to classify mushrooms as edible or poisonous using Python. Performed data preprocessing, feature engineering, and applied supervised learning algorithms such as Random Forest and Logistic Regression. Evaluated model performance using accuracy, precision, recall, and confusion matrix metrics. Delivered a robust model capable of predicting mushroom safety with high accuracy, providing a practical tool for educational and research purposes.