Large Scale K-Means Clustering with Gradient Descent

Learning with sequential, mini-batch, and batch data

Introduction

Clustering is an unsupervised form of a machine learning algorithm. It discovers sub-groups or patterns in the data. The K-Means algorithm is a simple and intuitive way to cluster data. When we apply the K-Means algorithm, we have to be mindful of dataset size and dimensionality. Either one of these can cause slow algorithmic convergence¹. In this article, we will explore gradient descent optimization and dimensionality …

clustering data science gradient k-means k-means-clustering machine learning optimization scale