Explore an end-to-end machine learning project with deployment, covering problem statement formulation, exploratory data analysis (EDA), and model training. Learn to handle exceptions, implement logging, perform feature engineering, and use Git for version control. Follow along with provided code examples and gain practical insights into developing and deploying a complete machine learning solution.