Mastering Random Forest Algorithms

Learn the fundamentals of the Random Forest algorithm, including decision trees, ensemble learning, bagging techniques, feature selection, model training, and performance evaluation. Explore real-world machine learning applications, classification and regression workflows, and practical implementation using Python and modern data science tools.