Principal Component Analysis, is one of the most useful data analysis and machine learning methods out there. It can be used to identify patterns in highly complex datasets and it can tell you what variables in your data are the most important. Lastly, it can tell you how accurate your new understanding of the data actually is.
In this video, I go one step at a time through PCA, and the method used to solve it, Singular Value Decomposition. I take it nice and slowly so that the simplicity of the method is revealed and clearly explained.
If you are interested in doing PCA in R see:
https://youtu.be/0Jp4gsfOLMsIf you are interested in learning more about how to determine the number of principal components, see:
https://youtu.be/oRvgq966yZgFor a complete index of all the StatQuest videos, check out:
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https://twitter.com/joshuastarmer0:00 Awesome song and introduction
0:30 Conceptual motivation for PCA
3:23 PCA worked out for 2-Dimensional data
5:03 Finding PC1
12:08 Singular vector/value, Eigenvector/value and loading scores defined
12:56 Finding PC2
14:14 Drawing the PCA graph
15:03 Calculating percent variation for each PC and scree plot
16:30 PCA worked out for 3-Dimensional data
#statquest #PCA #ML
About the Site π
This site provides links to random videos hosted at YouTube, with the emphasis on random. π₯
Origins of the Idea π±
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. π§
Challenges Faced π€
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. π
Creating Truly Random Links π οΈ
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube πΊ
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. π
Content and Users π΅
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact π€
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. π
List of ours generatorsβ‘
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