Principal Component Analysis (PCA)

Serrano.Academy February 10, 2019
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Serrano.Academy

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About

Welcome to Serrano.Academy! I'm Luis Serrano and I love demystifying concepts, capturing their essence, and sharing these videos with you. I prefer illustrations, analogies, and cartoons, rather than formulas (although we don't shy away from the math when needed). The topics I have are machine learning, mathematics (probability and statistics), but I'm open to many others. If you have any topics you'd like to suggest, feel free to add them in the comments or drop me a line! For more information, check out http://serrano.academy. And also check out my book! Grokking Machine Learning http://manning.com/books/grokking-machine-learning (40% discount code: serranoyt)

Video Description

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML 40% discount code: serranoyt A conceptual description of principal component analysis, including: - variance and covariance - eigenvectors and eigenvalues - applications As usual, very little formulas, lots and lots of pictures! 0:00 Introduction 0:46 Taking a picture 1:13 Dimensionality Reduction 2:02 Housing Data 5:09 Mean 7:46 Variance? 12:47 Covariance matrix 13:58 Linear Transformations 18:12 Eigenstuff 19:16 Eigenvalues 19:53 Eigenvectors 20:51 Principal Component Analysis (PCA) 26:05 Thank you!