In this video, we introduce k-Means, a clustering algorithm that won’t eat up all your laptop's computing power, making it, in some cases, a better choice than hierarchical clustering. For this introduction, we used Orange’s Interactive k-means widget found in the Education add-on. With it, we look at how k-Means goes about finding the optimal positions for its centroids. This video is a part of Introduction to Data Science video series that dives into machine learning, visual analytics, and joys of interactive data analysis using Orange Data Mining software ( ). SUBSCRIBE to our channel: The development of this video series was supported by grants from the Slovenian Research Agency (including P2-0209, V2-2274, and L2-3170), Slovenia Ministry of Digital Transformation, European Union (including xAIM and ARISA) and foundation. #machinelearning #orange #visualanalytics #datamining __ Written by: Blaž Zupan ( ) Presented by: Noah Novšak Production and edit: Lara Zupan Intro/outro: Agnieszka Rovšnik Music by: Damjan Jović – Dravlje Rec Orange is developed by Biolab at University of Ljubljana ( )