Foundations of Data Science - Lecture 8 - Low Rank Approximation (LRA) via Length Squared Sampling
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07.07.23 – 83849:01Опубликовано 12 декабря 2017, 17:12
Modern data often consists of feature vectors with a large number of features. High-dimensional geometry and Linear Algebra (Singular Value Decomposition) are two of the crucial areas which form the mathematical foundations of Data Science. This mini-course covers these areas, providing intuition and rigorous proofs. Connections between Geometry and Probability will be brought out.
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