Explores evaluation protocols in machine learning, including recall, precision, accuracy, and specificity, with real-world examples like COVID-19 testing.
Explores model evaluation with K-Nearest Neighbor, covering optimal k selection, similarity metrics, and performance metrics for classification models.
Explores the historical context and social aspects of scientific instruments, focusing on transparency, accuracy, solar microscopes, and scientific evolution.
