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Introduces unsupervised machine learning clustering techniques like K-means, Gaussian Mixture Models, and DBSCAN, explaining their algorithms and applications.
Delves into energy-saving design principles in wireless sensor networks, exploring motivating applications and intelligent algorithms for energy efficiency.
Covers the evaluation of clustering methods, including K-means clustering and the use of evaluation metrics to determine the optimal number of clusters.
