AI Concepts
DBSCAN can identify noise without choosing a cluster count first
DBSCAN builds clusters from local density and can leave points unassigned. Understand eps, min_samples and the limits before interpreting the labels.
AI · VISION · EVERYDAY SYSTEMS
AI Concepts
AI Concepts
Feature scaling changes what distance means to k-means clustering
K-means uses distances between feature values. A worked example shows how changing measurement scales can change the clusters a model finds.
AI Concepts
Multilabel classification lets one example belong to several classes
Multiclass and multilabel tasks have different assumptions. Decide whether an example may receive several labels before choosing data structures or evaluation.
AI Concepts
Reading Embeddings Without Inventing Names for Every Dimension
Understand an embedding as a learned numerical representation without assuming each coordinate has a tidy human-readable meaning.