[05x10] Clustering.jl: k-means Clustering | Julia Unsupervised Machine Learning

In this Julia Machine Learning coding tutorial, you'll get an Introduction to Unsupervised Machine Learning. You'll use the Clustering.jl package to apply the k-means Clustering algorithm to an Unlabeled data set.

- This tutorial is intended for students, hobbyists and amateurs.
- This tutorial is episode 10 of a 13-part series and is part of the Julia Machine Learning for Beginners playlist.
- Schedule: New tutorials are posted on Sundays / Mondays.
- Prerequisites: Julia, VS Code and Episodes 501 through 509.

00:00 Intro
06:00 Concepts
15:54 Application
24:02 Recap
26:31 Outro

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Links for this tutorial
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Code for this tutorial
https://github.com/julia4ta/tutorials...

Link to Clustering.jl (GitHub):
https://github.com/JuliaStats/Cluster...

Link to Clustering.jl (documentation):
https://juliastats.org/Clustering.jl/...

Link to Plots.jl (documentation):
https://docs.juliaplots.org/stable/

Link to RDatasets.jl (GitHub):
https://github.com/JuliaStats/RDatase...

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Links for this series
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Link to Series 5 Playlist [Julia Machine Learning for Beginners]
   • [05x01] What is Machine Learning?  

Andrew Ng's Stanford Machine Learning Course
Stanford CS229: Machine Learning | Autumn 2018
   • Stanford CS229: Machine Learning Cour...  

The Julia Programming Language
https://julialang.org/
https://docs.julialang.org/en/v1/
   / thejulialanguage  

VS Code
https://code.visualstudio.com/

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Notice of Non-Affiliation and Disclaimer:
I am not affiliated, associated, authorized, endorsed by, or in any way officially connected with Andrew Ng or Stanford University.
Nor am I affiliated, associated, authorized, endorsed by, or in any way officially connected with The Julia Programming Language, Julia Academy, Julia Computing, Microsoft, or any of their subsidiaries or their affiliates.
Nor am I affiliated, associated, authorized, endorsed by, or in any way officially connected with any software, packages or libraries used in this video.
All marks, emblems and images are registered trademarks of their respective owners. Use of them does not imply any affiliation with or endorsement by them.

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   / @doggodotjl  

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