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Explaining the Data Maps

Now that we have learned how to reduce data dimensionality and represent complex data in two dimensions we can discuss how to characterize the clusters that appear in our newly constructed visualizations. In this video we take a look at explaining clusters in data maps and finding features that distinguish between custer groups. 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 (https://orangedatamining.com). SUBSCRIBE to our channel:    / orangedatamining   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 Google.org/Tides foundation. #machinelearning #orange #visualanalytics #datamining __ Written by: Blaž Zupan (http://biolab.si/blaz) 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 (https://www.biolab.si)