Lindholm andreas (40 resultados)
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas,Wahlstrà m, Niklas,Lindsten, Fredrik,Schà n, Thomas B.
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Librería: Books From California, Simi Valley, CA, Estados Unidos de AmericaBooks From California
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EUR 33,56
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hardcover. Condición: Very Good. Cover and edges may have some wear.
Editorial: King Publishing, Laurence 2001
Librería: Better World Books Ltd, Dunfermline, Reino UnidoBetter World Books Ltd
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EUR 21,71
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Condición: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
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Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de AmericaRomtrade Corp.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 57,45
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Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Machine Learning : A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 60,29
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Condición: New.
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Librería: Textbooks_Source, Columbia, MO, Estados Unidos de AmericaTextbooks_Source
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EUR 59,09
Envío por EUR 3,48Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
hardcover. Condición: New. New. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
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- Primera edición
Librería: Prior Books Ltd, Cheltenham, , Reino UnidoPrior Books Ltd
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 38,57
Envío por EUR 25,35Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a… very nice book in great condition, now offered for sale at a reasonable price.
Machine Learning : A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
- Tapa dura
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 63,95
Envío por EUR 2,30Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: As New. Unread book in perfect condition.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 72,12
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 65,02
Envío por EUR 7,79Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 72,08
Envío por EUR 3,48Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Used. pp. 350 New edition niversity Press.
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 76,41
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Condición: New.
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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EUR 69,20
Envío por EUR 7,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Used. pp. 350.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 67,82
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Used. pp. 350.
Machine Learning : A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 65,00
Envío por EUR 17,28Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 7 disponibles
Condición: New.
Machine Learning: A First Course for Engineers and Scientists
Andreas Lindholm,Niklas Wahlstr�m,Fredrik Lindsten,Thomas B. Sch�n
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Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 66,40
Envío por EUR 17,85Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: New.
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
- Tapa dura
Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 72,44
Envío por EUR 13,80Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 7 disponibles
Condición: New. In.
Machine Learning: A First Course for Engineers and Scientists
Andreas Lindholm,Niklas Wahlstr�m,Fredrik Lindsten,Thomas B. Sch�n
- Tapa dura
Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 71,04
Envío por EUR 17,85Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: New.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 79,81
Envío por EUR 10,50Se envía de Irlanda a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2022. New. Hardcover. . . . . .
Machine Learning : A First Course for Engineers and Scientists
Lindholm, Andreas; Wahlström, Niklas; Lindsten, Fredrik; Schön, Thomas B.
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 75,28
Envío por EUR 17,28Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 7 disponibles
Condición: As New. Unread book in perfect condition.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 68,50
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Neuware -This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and log…istic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning. 338 pp. Englisch.
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, , AlemaniaRheinberg-Buch Andreas Meier eK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 68,50
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Neuware -This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and log…istic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning. 338 pp. Englisch.
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Librería: Wegmann1855, Zwiesel, , AlemaniaWegmann1855
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 68,50
Envío por EUR 25,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Neuware -This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and log…istic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
- Tapa dura
Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 102,48
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardback. Condición: New. This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic… regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
- Tapa dura
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 101,40
Envío por EUR 9,16Se envía dentro de Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. 2022. New. Hardcover. . . . . . Books ship from the US and Ireland.
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Librería: moluna, Greven, , Alemaniamoluna
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EUR 62,52
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Condición: New. This coherent introduction to machine learning for readers with a background in basic linear algebra, statistics, probability, and programming is suitable for advanced BSc or MSc courses. It covers theory and practice of basic and advanced methods such as d.
Machine Learning: A First Course for Engineers and Scientists
Lindholm, Andreas/ Wahlström, Niklas/ Lindsten, Fredrik/ Schön, Thomas B.
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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EUR 103,58
Envío por EUR 14,40Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: Brand New. 325 pages. 10.20x7.20x0.80 inches. In Stock.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 68,50
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Neuware -This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and log…istic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 338 pp. Englisch.
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Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 63,60
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Machine Learning | A First Course for Engineers and Scientists | Andreas Lindholm (u. a.) | Buch | Gebunden | Englisch | 2022 | Cambridge University Pr. | EAN 9781108843607 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 76,05
Envío por EUR 64,29Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. Neuware - This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and lo…gistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning.
- Tapa dura
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 136,11
Envío por EUR 32,29Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear…and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning. This coherent introduction to machine learning for readers with a background in basic linear algebra, statistics, probability, and programming is suitable for advanced BSc or MSc courses. It covers theory and practice of basic and advanced methods such as deep learning, Gaussian processes, random forests, support vector machines and boosting. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
