Tag: Machine Learning
-
The Invisible Math Behind Personalization – Part 2: When the shape of data matters
In Part 1, we measured distance the way a ruler does. Euclidean, Manhattan, Minkowski, Chebyshev, Canberra and Cosine all look at two customers, compare their numbers feature by feature, and return a single value. Rulers are honest, but they are also naive. A ruler does not know that long rides cost more, that airport trips…
-
The Invisible Math Behind Personalization: Notions of similarity or distance
Marketers face segmentation challenges by organizing various data entities like customers and products into actionable cohorts. Understanding how similar or different these entities are is crucial for effective decision-making. Distance and similarity metrics form the foundation of machine learning, enabling the transformation of raw data into valuable insights. Various algorithms utilize specific distance metrics, such…