Embark on a comprehensive 3-hour machine learning project tutorial in Hindi, tackling a real-world real estate problem from start to finish. Learn to collect and analyze data, import it into Jupyter notebooks, identify key attributes, find correlations, plot graphs, create pipelines, and handle missing values. Master essential concepts like cross-validation, train-test splitting, stratified shuffle split, and sampling through hands-on application. Develop a predictive model for house prices based on given features, presenting the solution to a simulated real estate company. Access accompanying source code, data, and Jupyter notebook to enhance your learning experience.