t-Distributed Stochastic Neighbor Embedding

In this video, we introduce t-distributed stochastic neighbor embedding, or t-SNE for short. We compare it to Multidimensional scaling (MDS). While the difference between the two methods is hard to spot using small datasets it becomes more pronounced with larger ones. We conclude that MDS preserves the distances between data points while t-SNE preserves each point’s neighbors.
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 (orangedatamining.com).
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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
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Written by: Blaž Zupan (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 (www.biolab.si)

[@deepinto8281]

Thank u for the brief explanation!!!

[@MukeshYadav-7897]

nice explanation , in neat and clean words , truly appreciated , can you please tell this software name which you are using

[@antoniogagliarducci]

orange xD