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Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9819801508 ISBN 13: 9789819801503
Da: Revaluation Books, Exeter, Regno Unito
EUR 83,54
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Aggiungi al carrelloPaperback. Condizione: Brand New. 320 pages. 3.94x3.94x2.36 inches. In Stock.
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EUR 138,89
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Aggiungi al carrelloCondizione: New.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9811299196 ISBN 13: 9789811299193
Da: Revaluation Books, Exeter, Regno Unito
EUR 166,70
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Aggiungi al carrelloHardcover. Condizione: Brand New. 320 pages. 3.94x3.94x2.36 inches. In Stock.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9819801508 ISBN 13: 9789819801503
Da: Revaluation Books, Exeter, Regno Unito
EUR 66,90
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Aggiungi al carrelloPaperback. Condizione: Brand New. 320 pages. 3.94x3.94x2.36 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, Singapore, 2025
ISBN 10: 9819801508 ISBN 13: 9789819801503
Da: CitiRetail, Stevenage, Regno Unito
EUR 79,33
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming. The first part addresses unconstrained optimization in single-variable and multivariable functions, introducing key algorithms such as steepest descent, Newton, and quasi-Newton methods.The second part focuses on constrained optimization, starting with linear equality constraints and extending to more general cases, including inequality constraints. It details optimality conditions, sensitivity analysis, and relevant algorithms for solving these problems.The third part covers linear programming, presenting the formulation of LP problems, the simplex algorithm, and sensitivity analysis. Throughout, the text provides numerous applications to data science, such as linear regression, maximum likelihood estimation, expectation-maximization algorithms, support vector machines, and linear neural networks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 89,83
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming. The first part addresses unconstrained optimization in single-variable and multivariable functions, introducing key algorithms such as steepest descent, Newton, and quasi-Newton methods.The second part focuses on constrained optimization, starting with linear equality constraints and extending to more general cases, including inequality constraints. It details optimality conditions, sensitivity analysis, and relevant algorithms for solving these problems.The third part covers linear programming, presenting the formulation of LP problems, the simplex algorithm, and sensitivity analysis. Throughout, the text provides numerous applications to data science, such as linear regression, maximum likelihood estimation, expectation-maximization algorithms, support vector machines, and linear neural networks.
Da: preigu, Osnabrück, Germania
EUR 91,40
Quantità: 5 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. CONTINUOUS OPTIMIZATION FOR DATA SCIENCE | Haviv Moshe | Taschenbuch | Englisch | 2025 | World Scientific | EAN 9789819801503 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: World Scientific Publishing Co Pte Ltd, Singapore, 2025
ISBN 10: 9811299196 ISBN 13: 9789811299193
Da: CitiRetail, Stevenage, Regno Unito
EUR 150,33
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming. The first part addresses unconstrained optimization in single-variable and multivariable functions, introducing key algorithms such as steepest descent, Newton, and quasi-Newton methods.The second part focuses on constrained optimization, starting with linear equality constraints and extending to more general cases, including inequality constraints. It details optimality conditions, sensitivity analysis, and relevant algorithms for solving these problems.The third part covers linear programming, presenting the formulation of LP problems, the simplex algorithm, and sensitivity analysis. Throughout, the text provides numerous applications to data science, such as linear regression, maximum likelihood estimation, expectation-maximization algorithms, support vector machines, and linear neural networks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Da: preigu, Osnabrück, Germania
EUR 147,00
Quantità: 5 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. CONTINUOUS OPTIMIZATION FOR DATA SCIENCE | Haviv Moshe | Buch | Englisch | 2025 | World Scientific | EAN 9789811299193 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 167,57
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming. The first part addresses unconstrained optimization in single-variable and multivariable functions, introducing key algorithms such as steepest descent, Newton, and quasi-Newton methods.The second part focuses on constrained optimization, starting with linear equality constraints and extending to more general cases, including inequality constraints. It details optimality conditions, sensitivity analysis, and relevant algorithms for solving these problems.The third part covers linear programming, presenting the formulation of LP problems, the simplex algorithm, and sensitivity analysis. Throughout, the text provides numerous applications to data science, such as linear regression, maximum likelihood estimation, expectation-maximization algorithms, support vector machines, and linear neural networks.