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Make Your Data Simpler with PCA

Principal Component Analysis (PCA) is a powerful technique for dimension reduction. transforming correlated features into principal components that capture most of the original data's variance. We deep dive into dimension reduction, pca, and singular value decomposition (SVD). 00:00 Curse of Dimensionality & Why Less Dimensions is Better 01:37 Dimension Reduction Intuition 03:08 Example & Explanation Using SVD 05:43 Things to Keep in Mind 07:20 Image Decompression 👍 Please like and comment if this video was helpful, and subscribe for more content! I also appreciate any suggestions on improving the video and further content. #ai #machinelearning #deeplearning #datascience --- Note I do not claim ownership of any assets including images used in the video. All visual content, trademarks, and media used are for educational purposes only. If you are the rightful owner of any material featured and have concerns, please contact me for removal or credit.