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Data science for mathematicians / Nathan Carter, ed.

Contributor(s): Material type: TextTextPublisher: Boca Raton, FL : CRC Press, 2020Edition: First editionDescription: volumes cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780367027056
  • 9780367528492
Subject(s): LOC classification:
  • QA300 .D3416 2020
Contents:
Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth.
Summary: "Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science"--
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Holdings
Item type Current library Call number Status Date due Barcode
Books - Printed PERPUSTAKAAN GUNASAMA HAB PENDIDIKAN TINGGI PAGOH QA300 .D3416 2020 (Browse shelf(Opens below)) Available SF0005335

Includes bibliographical references and index.

Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth.

"Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science"--

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