The Gaussian mixture model is a versatile clustering algorithm that addresses the limitations of methods like K-means by handling overlapping clusters and complex data distributions. Throughout this section, you saw its effectiveness on both synthetic and real-world datasets.

In summary, GMM provides a more robust solution for clustering tasks involving overlapping and non-spherical clusters, making it ideal for more complex datasets.