Koski Timo (23 results)

Hardcover. Condition: Very Good. 1st Edition. Light pencil underlining in small part of text. Could be erased if one desired. ***Shipped within 24 hours from the beautiful Baltimore inner harbor area. First class service; accurate descriptions. Most items packed in boxes, not envelopes.***. Book.

Hardcover. Condition: Very Good+. First Edition Thus. A tight and clean copy. Interior pages clean and unmarked. Photos upon request. International shipping billed at cost.; Large 8vo 9" - 10" tall; 368 pages.

2009.Hardcover.Very good condition.347 pages.Ships from Japan.Usually ships in 1-2 working days.

Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 92 KOS 9781402001369 Sprache: Englisch Gewicht in Gramm: 550.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: new. Hardcover. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications.A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods.A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning.All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: new.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. pp. viii + 347 Illus.

Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:9780470743041.

Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,850grams, ISBN:9780470743041.

Hardback. Condition: New. New copy - Usually dispatched within 4 working days.

Condition: New. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Series: Wiley Series in Probability and Statistics. Num Pages: 366 pages, Illustrations. BIC Classification: PBT. Category: (U) Tertiary Education (US: College); (UU) Undergraduate. Dimension: 253 x 176 x 26. Weight in Grams: 788. . 2009. 1st Edition. Hardcover. . . . .

Condition: New. pp. viii + 347 Index.

Hardcover. Condition: Brand New. 1st edition. 366 pages. 10.00x6.75x1.00 inches. In Stock.

Hardcover. Condition: new. Hardcover. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications.A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods.A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning.All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Series: Wiley Series in Probability and Statistics. Num Pages: 366 pages, Illustrations. BIC Classification: PBT. Category: (U) Tertiary Education (US: College); (UU) Undergraduate. Dimension: 253 x 176 x 26. Weight in Grams: 788. . 2009. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Condition: new. Hardcover. Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications.A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods.A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning.All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest. Bayesian networks have found application in a number of fields, including risk analysis, consumer help desks, tissue pathology, pattern recognition, credit assessment, computer network diagnosis, and artificial intelligence. Bayesian Networks is a self-contained introduction to the theory and applications of Bayesian networks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New. Gives a thorough and systematic introduction to probabilistic modeling in bioinformatics. This book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. It also gives examples of known architectures (such as, profile HMM) used in genome analysis. Series: Computational Biology. Num Pages: 408 pages, biography. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 23. Weight in Grams: 758. . 2001. Hardback. . . . .

Condition: New. Gives a thorough and systematic introduction to probabilistic modeling in bioinformatics. This book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. It also gives examples of known architectures (such as, profile HMM) used in genome analysis. Series: Computational Biology. Num Pages: 408 pages, biography. BIC Classification: PBT; PSAK. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 23. Weight in Grams: 758. . 2001. Hardback. . . . . Books ship from the US and Ireland.

Condition: Very Good. A clean copy with paper wraps and no previous owners' names or other defacements. Written in English. 6.25 x 9.25 in (15.75 x 23.5 cm).