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dc.contributor.authorAvrim Blum-
dc.date.accessioned2023-05-15T04:22:33Z-
dc.date.available2023-05-15T04:22:33Z-
dc.date.issued2020-
dc.identifier.urihttp://thuvienso.thanglong.edu.vn//handle/TLU/6643-
dc.description.abstractThis book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensingvi
dc.language.isoenvi
dc.publisherCambridge: Cambridge University Pressvi
dc.subjectComputer science | Statistics | Quantitative research | Khoa học máy tínhvi
dc.titleFoundations of data sciencevi
dc.typeSách/Bookvi
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