Abstract ( Time Series Clustering ) In order to understand Time Series Clustering we need to understand the time series data, characterized by sequential observations over time, which is ubiquitous in domains such as system monitoring, finance, and IoT. While forecasting is a common analytical goal, understanding inherent patterns across multiple time series is equally critical. Time series clustering, an unsupervised machine learning technique, groups similar temporal behaviors, enabling pattern discovery and anomaly detection without prior labels. This blog post, tailored for an academic lab session, explores time series clustering using Dynamic Time Warping (DTW) in R to analyze endpoint…