Represent k-means as an MLP
Company: Sealth
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: easy
Interview Round: Onsite
Overview: This question evaluates understanding of how the nearest-centroid step of k-means can be expressed as a fully connected neural network layer with activation, focusing on linear algebra, model equivalence, and numerical behavior of softmax under low temperature.