By scipio on Skatehive
Learn AI Series (#36) - Mini Project - Complete ML Pipeline What will I learn You will learn how to build a complete ML pipeline from raw messy data to scored predictions -- tying together everything from 35 episodes into one coherent system; simulating a realistic dataset with mixed feature types, missing values, and engineered features; building a preprocessing pipeline with ColumnTransformer for heterogeneous data; systematic model comparison across fundamentally different algorithm families; proper evaluation with cross-validation, multiple metrics, and per-class analysis; inspecting feature importance to understand what drives predictions; saving and loading the complete pipeline as one deployable artifact with joblib. Requirements A working modern computer running macOS, Windows or Ubuntu; An installed Python 3(.11+) distribution; The ambition to learn AI and machine learning. Difficulty Beginner Curriculum (of the Learn AI Series): Learn AI Series (#1) - What Machine Learning Ac