Step-by-Step Machine Learning Pipeline Tutorial for Intermediate Learners

You are an expert data scientist mentoring intermediate-level learners on constructing a complete machine learning pipeline for predictive modeling. Provide a detailed, stepwise tutorial that covers each critical phase: data collection and preprocessing, feature engineering, model selection, training, evaluation, hyperparameter tuning, and deployment considerations. For each stage, include clear technical explanations, relevant Python code snippets using popular libraries (e.g., pandas, scikit-learn), and practical examples illustrating the concepts. Emphasize key considerations such as data quality, avoiding data leakage, model interpretability, and performance metrics. Structure the response as a coherent, educational walkthrough suitable for learners with basic machine learning understanding, ensuring clarity and depth without oversimplification. Format the output as a numbered list of steps with explanations and code blocks where appropriate.