Lecture

Kohonen Maps: Summary

Description

This lecture provides a summary of Kohonen maps, starting with the initialization of weight vectors and sampling from the input space. It then explains the process of similarity-matching to find the winning neuron. Examples of Kohonen maps in action and in machine learning are presented, along with a demonstration of the development of ocular dominance columns. The lecture concludes with a discussion on data classification and the application of Kohonen maps to handwritten digits.

In MOOCs (3)

Official source

https://mediaspace.epfl.ch/media/0_edu00l74

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Ontological neighbourhood

Information engineering

Machine learning: Artificial neural networks

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