Foundations of Data Science by Avrim Blum HARDBACK 9781108485067
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Foundations of Data Science\nby Avrim Blum\nHardback\nEnglish\n\nDelivery\nUsually delivered in 2\u20133 working days (dispatched today if ordered before 3pm).\n\nBrand new copy from BookCurl \u2013 the UK independent online bookseller.\n\n------------------------------\nBook details\n------------------------------\nAuthor: Avrim Blum\nTitle: Foundations of Data Science\nFormat: Hardback\nLanguage: English\nTopic: Pattern recognition\nPublisher: Cambridge University Press\nPublication year: 2020\nISBN-13: 9781108485067\nISBN-10: 1108485065\n\n------------------------------\nDescription\n------------------------------\nThis 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 .
Foundations of Data Science by Avrim Blum HARDBACK 9781108485067
Foundations of Data Science\nby Avrim Blum\nHardback\nEnglish\n\nDelivery\nUsually delivered in 2\u20133 working days (dispatched today if ordered before 3pm).\n\nBrand new copy from BookCurl \u2013 the UK independent online bookseller.\n\n------------------------------\nBook details\n------------------------------\nAuthor: Avrim Blum\nTitle: Foundations of Data Science\nFormat: Hardback\nLanguage: English\nTopic: Pattern recognition\nPublisher: Cambridge University Press\nPublication year: 2020\nISBN-13: 9781108485067\nISBN-10: 1108485065\n\n------------------------------\nDescription\n------------------------------\nThis 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 .
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