unsupervised learning

  • k-means-clustering – Entwicklung mit Scratch

    K-means-clustering – development with Scratch

    K-Means Clustering is a popular algorithm in the field of unsupervised learning, which is used to divide data into groups or clusters. This approach makes it possible to identify patterns in data without requiring prior labels. For an introduction to the topic and a fun board game to illustrate the concepts of unsupervised learning, you can find information on this page. There you will find materials that help you better understand the basics of K-Means Clustering and apply them in practice.

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