Foundations of Data Science - Lecture 5 - Length Squared Sampling in Matrices

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Microsoft Research
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Published on ● Video Link: https://www.youtube.com/watch?v=M1nRLD4wKk8


Duration: 1:14:00
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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.

See more at https://www.microsoft.com/en-us/research/video/foundations-of-data-science-lecture-5-length-squared-sampling-in-matrices/



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Tags:
microsoft research
foundations of data science
probability
geometry