Topic Overview

K-Means is a popular clustering algorithm. Clustering algorithms fall into the category unsupervised learning. As such, K-Means sorts input data into a parameterizable set of clusters.

This topic is a wrapper around training material that originates from an inhouse training given to a company specializing in spectral image analysis; the hard- and software they create is used to classify chunks of material running by on a conveyor belt. The topic artifacts might contain terminology from their problem domain (a lot of MATLAB stuff).

The problem is demonstrated not by dealing with spectral images with 256 planes, but by color-reducing this PNG image


to this



Like Linear Regression, this topic consists of

Topic Dependencies

cluster_python Python Programming: From Absolute Beginner to Advanced Productivity cluster_python_swdev Python: Project/Package Management cluster_python_misc Python: Miscellaneous Topics cluster_python_misc_ai Machine Learning, Artificial Intelligence cluster_python_advanced Python: More Language Features python_swdev_pip Python Package Index python_misc_import The import Statement (incomplete) python_swdev_pip->python_misc_import python_swdev_venv Virtual Environments python_swdev_venv->python_swdev_pip python_swdev_venv->python_misc_import python_advanced_modules Modules and Packages python_misc_import->python_advanced_modules python_misc_ai_machine_learning_intro Machine Learning: Concepts and Terminology python_misc_ai_linear_regression Linear Regression python_misc_ai_linear_regression->python_swdev_venv python_misc_ai_linear_regression->python_misc_ai_machine_learning_intro python_misc_ai_k_means K-Means python_misc_ai_k_means->python_swdev_venv python_misc_ai_k_means->python_misc_ai_machine_learning_intro python_misc_ai_k_means->python_misc_ai_linear_regression