Ali Ghodsi, Lec 4: MDS, Isomap, LLE
Ali Ghodsi's lecture on January 17, 2017 for STAT 442/842: Data Visualization, held at the University of Waterloo. Review of Multidimensional Scaling (MDS) . Introduction to Isomap algorithm. Introduction to Locally Linear Embedding (LLE) algorithm. LLE weight optimization problem.
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Ali Ghodsi, Lec 5: LLE, Spectral Clustering
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8.6 David Thompson (Part 6): Nonlinear Dimensionality Reduction: KPCA
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Shape Analysis (Lecture 11): Structure-preserving embedding (ISOMAP, LLE); manifold learning
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Ali Ghodsi, Lec 1: Principal Component Analysis
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The Tale of a Success with Ali Ghodsi
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Ali Ghodsi, Lec 13: Word2Vec Skip-Gram
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Ali Ghodsi, Lec 4: PCA,Fisher's Discriminant Analysis (FDA)
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Richard Feynman. Why.
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Multidimensional Scaling (MDS) | Dimensionality Reduction Techniques (3/5)
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The Most Important Algorithm in Machine Learning
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Ali Ghodsi, Lec 15: t-SNE
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16. Learning: Support Vector Machines
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Statistical Machine Learning Part 30 - Isomap
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Locally Linear Embedding
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The best stats you've ever seen | Hans Rosling
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Ali Ghodsi, Lec 14: Autoencoders, Clustering, Mixture of Gaussians
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Support Vector Machines Part 1 (of 3): Main Ideas!!!
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Ali Ghodsi, Lec 9: SPCA, Nystrom Approximation, NMF
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