Order Total (1 Item Items):
Shipping Destination:
Cause Effect Pairs Machine (28 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (28)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (26)
- As New, Fine or Near Fine (1)
- Very Good or Good (No further results match this refinement)
- Fair or Poor (No further results match this refinement)
- As Described (1)
Binding
Collectible Attributes
- First Edition (No further results match this refinement)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (9)
- Not Print on Demand (16)
Language (1)
Free Shipping
Seller Location
Seller Rating
-
Hardcover. Condition: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
-
Cause Effect Pairs in Machine Learning.
Book 7 of 8: The Springer Series on Challenges in Machine LearningSeller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Association Member: GIAQ ILAB VDA
Seller rating 4 out of 5 stars
XVI, 372 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. The Springer Series on Challenges in Machine Learning. Sprache: Englisch.
-
Cause Effect Pairs in Machine Learning (The Springer Series on Challenges in Machine Learning)
Book 7 of 8: The Springer Series on Challenges in Machine LearningSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 85.99
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Condition: New. pp. XVI, 372 122 illus., 90 illus. in color. 1 Edition NO-PA16APR2015-KAP.
-
Cause Effect Pairs In Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
-
Cause Effect Pairs in Machine Learning (The Springer Series on Challenges in Machine Learning)
Book 7 of 8: The Springer Series on Challenges in Machine LearningSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 116.47
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer-Nature New York Inc, 2020
ISBN 10: 3030218120 ISBN 13: 9783030218126
Paperback. Condition: Brand New. 388 pages. 9.25x6.10x0.94 inches. In Stock.
-
-
Taschenbuch. Condition: Neu. Cause Effect Pairs in Machine Learning | Isabelle Guyon (u. a.) | Taschenbuch | xvi | Englisch | 2020 | Springer | EAN 9783030218126 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, Springer International Publishing, 2020
ISBN 10: 3030218120 ISBN 13: 9783030218126
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents ground-breaking advances in the domain of causal structure learning.The problem of distinguishing cause from effect('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of theChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.This book provides both tutorial material on the state-of-the-art on cause-effect pairs and exposes the reader to more advanced material, with a collection of selected papers. Supplemental material includes videos, slides, and code which can be found on the workshop website.Discovering causal relationships from observational data will become increasingly important in data science with the increasing amount of available data, as a means of detecting potential triggers in epidemiology, social sciences, economy, biology, medicine, and other sciences.
-
Condition: New. pp. XVI, 372 122 illus., 90 illus. in color. 1 Edition NO-PA16APR2015-KAP.
-
-
Cause Effect Pairs In Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, Springer Nature Switzerland, 2019
ISBN 10: 3030218090 ISBN 13: 9783030218096
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents ground-breaking advances in the domain of causal structure learning.The problem of distinguishing cause from effect('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of theChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.This book provides both tutorial material on the state-of-the-art on cause-effect pairs and exposes the reader to more advanced material, with a collection of selected papers. Supplemental material includes videos, slides, and code which can be found on the workshop website.Discovering causal relationships from observational data will become increasingly important in data science with the increasing amount of available data, as a means of detecting potential triggers in epidemiology, social sciences, economy, biology, medicine, and other sciences.
-
Hardcover. Condition: Brand New. 372 pages. 9.25x6.25x1.00 inches. In Stock.
-
-
Condition: new. Questo è un articolo print on demand.
-
Condition: new. Questo è un articolo print on demand.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, Springer International Publishing Nov 2020, 2020
ISBN 10: 3030218120 ISBN 13: 9783030218126
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents ground-breaking advances in the domain of causal structure learning.The problem of distinguishing cause from effect('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of theChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.This book provides both tutorial material on the state-of-the-art on cause-effect pairs and exposes the reader to more advanced material, with a collection of selected papers. Supplemental material includes videos, slides, and code which can be found on the workshop website.Discovering causal relationships from observational data will become increasingly important in data science with the increasing amount of available data, as a means of detecting potential triggers in epidemiology, social sciences, economy, biology, medicine, and other sciences. 388 pp. Englisch.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, 2020
ISBN 10: 3030218120 ISBN 13: 9783030218126
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive reference for those interested in the cause-effect problem, and how to tackle them using machine learning algorithmsIncludes six tutorial chapters, beginning with the simplest cases and common methods, to alg.
-
Condition: New. Print on Demand pp. XVI, 372 122 illus., 90 illus. in color.
-
Condition: New. PRINT ON DEMAND pp. XVI, 372 122 illus., 90 illus. in color.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer, Springer Nov 2020, 2020
ISBN 10: 3030218120 ISBN 13: 9783030218126
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect ('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of the ChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 388 pp. Englisch.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, Springer Nature Switzerland Nov 2019, 2019
ISBN 10: 3030218090 ISBN 13: 9783030218096
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents ground-breaking advances in the domain of causal structure learning.The problem of distinguishing cause from effect('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of theChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.This book provides both tutorial material on the state-of-the-art on cause-effect pairs and exposes the reader to more advanced material, with a collection of selected papers. Supplemental material includes videos, slides, and code which can be found on the workshop website.Discovering causal relationships from observational data will become increasingly important in data science with the increasing amount of available data, as a means of detecting potential triggers in epidemiology, social sciences, economy, biology, medicine, and other sciences. 388 pp. Englisch.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, 2019
ISBN 10: 3030218090 ISBN 13: 9783030218096
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive reference for those interested in the cause-effect problem, and how to tackle them using machine learning algorithmsIncludes six tutorial chapters, beginning with the simplest cases and common methods, to alg.
-
Condition: New. Print on Demand pp. XVI, 372 122 illus., 90 illus. in color.
-
Condition: New. PRINT ON DEMAND pp. XVI, 372 122 illus., 90 illus. in color.
-
Cause Effect Pairs in Machine Learning
Book 7 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer, Springer Nov 2019, 2019
ISBN 10: 3030218090 ISBN 13: 9783030218096
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents ground-breaking advances in the domain of causal structure learning. The problem of distinguishing cause from effect ('Does altitude cause a change in atmospheric pressure, or vice versa ') is here cast as a binary classification problem, to be tackled by machine learning algorithms. Based on the results of the ChaLearn Cause-Effect Pairs Challenge, this book reveals that the joint distribution of two variables can be scrutinized by machine learning algorithms to reveal the possible existence of a 'causal mechanism', in the sense that the values of one variable may have been generated from the values of the other.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 388 pp. Englisch.
