By scipio on Skatehive
Learn AI Series (#33) - Ensemble Methods Deep Dive - Stacking and Blending What will I learn You will learn stacking -- training a meta-learner on top of base model predictions to squeeze out extra accuracy; blending -- a simpler stacking variant that uses a holdout set in stead of cross-validation; voting classifiers -- hard vs soft voting and when each helps; the mixture of experts concept -- routing inputs to specialized models; why model diversity matters more than individual model accuracy; practical strategies for building competition-winning ensembles; when ensembles are worth the added complexity (and when they're absolutely not). 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 Actually Is Learn AI Series (#2) - Setting Up Your AI Workbench - Python and NumPy Learn