Foundations of Data Science
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Foundations of Data Science
Foundations of Data Science*Avrini Blum, John Hopcroft, and Ravindran Kannan Thursday 1th January, 2018•Copyright 2015. -All rights reserved1Contents1 Foundations of Data Science 1Introduction92High-Dimensional Space122.1Introduction........................................................ 122.2The Law of Large Numbers............................................ 122.3The Geomet ry of High Dimensions.................................... 152.4Properties of the Unit Ball......... Foundations of Data Science ................................ 172.4.1Volume of the Unit Ball....................................... 172.4.2Volume Near the Equator.................Foundations of Data Science
...................... 192.5Generating Points Uniformly at Random froma Ball................... 222.6Gaussians in High Dimension......................Foundations of Data Science*Avrini Blum, John Hopcroft, and Ravindran Kannan Thursday 1th January, 2018•Copyright 2015. -All rights reserved1Contents1 Foundations of Data Science ................ 272.9Fitting a spherical Gaussian to Data................................ 292.1Bibliographic Noles................................................ 312.11Exercises.......................................................... 323Best-Fit Subspaces and SingularValue Decomposition (SVD)403 Foundations of Data Science .1Introduction.................................1.1.................... 403.2Preliminaries ...................................................... 413.3Foundations of Data Science
Singular Vectors.................................................... 423.4Singular Value Decomposition (SVD).................................. 453.5BeFoundations of Data Science*Avrini Blum, John Hopcroft, and Ravindran Kannan Thursday 1th January, 2018•Copyright 2015. -All rights reserved1Contents1 Foundations of Data Science r Method for Singular Value Decomposition....................... 513.7.1A Faster Method............................................... 513.8Singular Vectors and Eigenvectors................................... 543.9Applications of Singular Value Decomposition........................ 543.9.1Centering Foundations of Data Science Data................................................ 543.9.2Principal Component Analysis.................................. 563.9.3Clustering a MixtureFoundations of Data Science
of Spherical Gaussians................... 563.9.4Ranking Documents and Web Pages .............................. 623.9.5An Application of SVD to a DisFoundations of Data Science*Avrini Blum, John Hopcroft, and Ravindran Kannan Thursday 1th January, 2018•Copyright 2015. -All rights reserved1Contents1Foundations of Data Science*Avrini Blum, John Hopcroft, and Ravindran Kannan Thursday 1th January, 2018•Copyright 2015. -All rights reserved1Contents1Gọi ngay
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