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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New.
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Optimization for Data Analysis (Hardback or Cased Book)
Published by Cambridge University Press 4/5/2022, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Hardback or Cased Book. Condition: New. Optimization for Data Analysis 1.07. Book.
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OPTIMIZATION FOR DATA ANALYSIS
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 54.44
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New. SUPER FAST SHIPPING.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: As New. Unread book in perfect condition.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New.
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Optimization for Data Analysis (Hardcover)
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Hardcover. Condition: new. Hardcover. Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks. Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundamentals of optimization algorithms, focusing on the techniques most relevant to data science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 59.69
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 69.26
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 65.72
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Optimization for Data Analysis
Published by Cambridge University Press 2021-10-31, 2021
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 57.97
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Optimization for Data Analysis
Published by Cambridge University Press, GB, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
US$ 77.63
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Add to basketHardback. Condition: New. Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
US$ 72.18
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Add to basketCondition: New. 2022. New. Hardcover. . . . . .
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 65.80
Convert currencyUS$ 20.44 shipping from United Kingdom to U.S.A.Quantity: 2 available
Add to basketCondition: As New. Unread book in perfect condition.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Condition: New. 2022. New. Hardcover. . . . . . Books ship from the US and Ireland.
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International EditionUS$ 95.85
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Add to basketHardcover. Condition: Brand New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-11 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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OPTIMIZATION FOR DATA ANALYSIS
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 53.21
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US$ 84.30
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Add to basketHardcover. Condition: Brand New. 227 pages. 9.25x6.25x0.75 inches. In Stock.
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Optimization for Data Analysis (Hardcover)
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 69.47
Convert currencyUS$ 50.43 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks. Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundamentals of optimization algorithms, focusing on the techniques most relevant to data science. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Optimization for Data Analysis (Hardcover)
Published by Cambridge University Press, Cambridge, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 90.22
Convert currencyUS$ 37.00 shipping from Australia to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks. Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundamentals of optimization algorithms, focusing on the techniques most relevant to data science. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Optimization for Data Analysis
Published by Cambridge University Pr., 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 69.70
Convert currencyUS$ 57.93 shipping from Germany to U.S.A.Quantity: 1 available
Add to basketCondition: New. Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for students, researchers, and practitioners. This compact, self-contained text covers the fundam.
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Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 71.14
Convert currencyUS$ 73.92 shipping from Germany to U.S.A.Quantity: 2 available
Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks.
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Optimization for Data Analysis
Published by Cambridge University Press, GB, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
US$ 73.99
Convert currencyUS$ 88.59 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardback. Condition: New. Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental properties provides important grounding for students, researchers, and practitioners in these areas. This text covers the fundamentals of optimization algorithms in a compact, self-contained way, focusing on the techniques most relevant to data science. An introductory chapter demonstrates that many standard problems in data science can be formulated as optimization problems. Next, many fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization of smooth (especially convex) functions; the stochastic gradient method, a workhorse algorithm in machine learning; the coordinate descent approach; several key algorithms for constrained optimization problems; algorithms for minimizing nonsmooth functions arising in data science; foundations of the analysis of nonsmooth functions and optimization duality; and the back-propagation approach, relevant to neural networks.
-
Optimization for Data Analysis
Published by Cambridge University Press, 2022
ISBN 10: 1316518981 ISBN 13: 9781316518984
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 57.73
Convert currencyUS$ 16.01 shipping from United Kingdom to U.S.A.Quantity: 5 available
Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
