Principal Component Analysis (PCA) Explained

Principal component analysis (PCA) is a workhorse algorithm in statistics, where dominant correlation patterns are extracted from high-dimensional data.

Steve Brunton explains it in this great video.

Frank

#DataScientist, #DataEngineer, Blogger, Vlogger, Podcaster at http://DataDriven.tv . Back @Microsoft to help customers leverage #AI Opinions mine. #武當派 fan. I blog to help you become a better data scientist/ML engineer Opinions are mine. All mine.