Advanced Machine Learning Table of contents Table of contents Part A. General 1. Introduction 2. Data Pre-Processing 3. Transformation Pipeline 4. EDA 5. Feature Engineering 6. Evaluation Metrics 7. Model Fine-Tuning 8. Model Deployment Part B. Machine Learning Models 1. Linear Regression 2. Logistic Regression 3. Bayes Learning 4. Ensemble methods Part C. Interview Questions 1. Statistics 2. Technical Terms Resources Hands-On Machine Learning with Scikit-Learn and TensorFlow Essence of Linear Algebra Data Science Portfolio (Back to top)