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Introduction of Kernel Pca
Welcome to Lecture 9 of the course "Machine Learning Techniques" by Prof. Arun Rajkumar. Full Course: ... Part of the Course "Statistical Machine Learning", Summer Term 2020, Ulrike von Luxburg, University of Tübingen. 1) Motivation & Methods of Dimensionality Reduction 2) Principal Component Analysis (PCA) 3) Discussion of concepts of issues with PCA and algorithm to overcome those issues. A detailed discussion on SVM can only produce linear boundaries between classes by default, which not enough for most machine learning applications. In this video you will learn about three very common methods for data dimensionality reduction:
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Last Updated: May 24, 2026
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