Foundations of Data Science - Lecture 5 - Length Squared Sampling in Matrices
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Microsoft Research334 тыс
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12.12.17 – 3 2721:19:15Популярные
88 дней – 1 5691:23:36
Опубликовано 12 декабря 2017, 4:19
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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