Editore: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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ISBN 10: 1009303864 ISBN 13: 9781009303866
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ISBN 10: 1009303864 ISBN 13: 9781009303866
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ISBN 10: 1009303864 ISBN 13: 9781009303866
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Aggiungi al carrelloCondizione: New. Über den AutorAlex Gezerlis is Professor of Physics at the University of Guelph. Before moving to Canada, he worked in Germany, the United States, and Greece. He has received several research awards, grants, and allocations on super.
Editore: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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Editore: Cambridge University Press 2023-04-30, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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ISBN 10: 1009303864 ISBN 13: 9781009303866
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - 'Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this book covers linear algebra, differential equations, root-finding, interpolation, and integration. Fully implementing many numerical methods in Python and with 140 new problems, it is an ideal standalone textbook on computational physics'--.
Editore: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
Lingua: Inglese
Da: Kennys Bookstore, Olney, MD, U.S.A.
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Editore: Cambridge University Press, Cambridge, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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Da: CitiRetail, Stevenage, Regno Unito
EUR 65,65
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this book covers linear algebra, differential equations, root-finding, interpolation, and integration. Fully implementing many numerical methods in Python and with 140 new problems, it is an ideal standalone textbook on computational physics. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Editore: Cambridge University Press, 2020
ISBN 10: 1108738931 ISBN 13: 9781108738934
Lingua: Inglese
Da: Books From California, Simi Valley, CA, U.S.A.
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ISBN 10: 1009303864 ISBN 13: 9781009303866
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Editore: Cambridge University Press, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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Aggiungi al carrellopaperback. Condizione: New. 2nd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Editore: Cambridge University Press, 2020
ISBN 10: 1108738931 ISBN 13: 9781108738934
Lingua: Inglese
Da: Bookmans, Tucson, AZ, U.S.A.
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Editore: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
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EUR 107,21
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Editore: Cambridge University Press, Cambridge, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
Lingua: Inglese
Da: Grand Eagle Retail, Mason, OH, U.S.A.
EUR 72,36
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this book covers linear algebra, differential equations, root-finding, interpolation, and integration. Fully implementing many numerical methods in Python and with 140 new problems, it is an ideal standalone textbook on computational physics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
Lingua: Inglese
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 125,04
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Editore: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
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EUR 119,49
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ISBN 10: 1009303856 ISBN 13: 9781009303859
Lingua: Inglese
Da: California Books, Miami, FL, U.S.A.
EUR 143,09
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Editore: Cambridge University Press, Cambridge, 2023
ISBN 10: 1009303864 ISBN 13: 9781009303866
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Da: AussieBookSeller, Truganina, VIC, Australia
EUR 120,76
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject. Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this book covers linear algebra, differential equations, root-finding, interpolation, and integration. Fully implementing many numerical methods in Python and with 140 new problems, it is an ideal standalone textbook on computational physics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
Lingua: Inglese
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 140,72
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Editore: Cambridge University Press, 2023
ISBN 10: 1009303856 ISBN 13: 9781009303859
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 148,58
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Aggiungi al carrelloGebunden. Condizione: New. Über den AutorAlex Gezerlis is Professor of Physics at the University of Guelph. Before moving to Canada, he worked in Germany, the United States, and Greece. He has received several research awards, grants, and allocations on super.