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Mini Course #2 (Part1): A Visual Introduction to Geometric Data Analysis

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Mini Course #2 (Part1): A Visual Introduction to Geometric Data Analysis
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13
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CC Attribution - NonCommercial - NoDerivatives 4.0 International:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Release Date2021
LanguageEnglish

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Abstract
We give a visual introduction to several geometric techniques for analyzing data. These include both unsupervised learning (clustering, dimensionality reduction, topic modeling), and supervised learning (k-nearest neighbors, support vector machines), though we don't expect you to know what any of those words mean! The goal is to distill the methods down to visual and oral description without mathematical notation. The performance of data analysis techniques will be illustrated on real-world image and text datasets. Mini-course participants will be encouraged to develop their own purely visual explanations