Introduction Vector Quantization (VQ) is a pivotal technique in machine learning and data compression that maps high-dimensional data points into a discrete set of values called codes. It plays a critical role in reducing the computational complexity of models while maintaining a high level of accuracy. This article explores VQ through the lens of observation, … Continue reading Vector Quantization: observation, codes, and diff in Machine Learning Models