Explainable interpretable models computer (15 résultats)
Langue : anglais
Edité par Cham, Springer., 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, AllemagneUniversitätsbuchhandlung Herta Hold GmbH
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Occasion
EUR 12,00
EUR 30,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 5 disponible(s)
XVII, 299 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: Englis…ch.
Langue : anglais
Edité par Springer, 2019
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion - Très bon
EUR 59,90
EUR 60,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Gebundene Ausgabe. Etat : Sehr gut. Gebraucht - Sehr gut - ungelesen,als Mängelexemplar gekennzeichnet, mit leichten Mängeln an Schnitt oder Einband durch Lager- oder Transportschaden -This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer visio…n and machine learning.Springer Fachmedien Wiesbaden GmbH, Abraham-Lincoln-Str. 46, 65189 Wiesbaden 316 pp. Englisch.
Langue : anglais
Edité par Springer International Publishing, 2019
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : moluna, Greven, Allemagnemoluna
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 78,85
EUR 48,99 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : New. Presents a snapshot of explainable and interpretable models in the context of computer vision and machine learningCovers fundamental topics to serve as a reference for newcomers to the fieldOffers successful methodologies, with appli.
Langue : anglais
Edité par Springer-Verlag GmbH, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-UniPBShop.store UK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 133,82
EUR 5,90 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
UNK. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Langue : anglais
Edité par Springer-Verlag GmbH, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Buchpark, Trebbin, AllemagneBuchpark
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion
EUR 36,59
EUR 105,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : Hervorragend. Zustand: Hervorragend | Seiten: 299 | Sprache: Englisch | Produktart: Bücher | This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition h…as led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning· Explanation Methods in Deep Learning· Learning Functional Causal Models with Generative Neural Networks· Learning Interpreatable Rules for Multi-Label Classification· Structuring Neural Networks for More Explainable Predictions· Generating Post Hoc Rationales of Deep Visual Classification Decisions· Ensembling Visual Explanations· Explainable Deep Driving by Visualizing Causal Attention· Interdisciplinary Perspective on Algorithmic Job Candidate Search· Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations.
Langue : anglais
Edité par Springer-Verlag Gmbh Sep 2018, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture souple
Vendeur : Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AllemagneRheinberg-Buch Andreas Meier eK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 160,49
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. Neuware -This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like…performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made what in the model structure explains its functioning Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: Evaluation and Generalization in Interpretable Machine Learning Explanation Methods in Deep Learning Learning Functional Causal Models with Generative Neural Networks Learning Interpreatable Rules for Multi-Label Classification Structuring Neural Networks for More Explainable Predictions Generating Post Hoc Rationales of Deep Visual Classification Decisions Ensembling Visual Explanations Explainable Deep Driving by Visualizing Causal Attention Interdisciplinary Perspective on Algorithmic Job Candidate Search Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions Inherent Explainability Pattern Theory-based Video Event Interpretations 299 pp. Englisch.
Langue : anglais
Edité par Springer-Verlag Gmbh Sep 2018, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture souple
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 160,49
EUR 23,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Taschenbuch. Etat : Neu. Neuware -This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like…performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made what in the model structure explains its functioning Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: Evaluation and Generalization in Interpretable Machine Learning Explanation Methods in Deep Learning Learning Functional Causal Models with Generative Neural Networks Learning Interpreatable Rules for Multi-Label Classification Structuring Neural Networks for More Explainable Predictions Generating Post Hoc Rationales of Deep Visual Classification Decisions Ensembling Visual Explanations Explainable Deep Driving by Visualizing Causal Attention Interdisciplinary Perspective on Algorithmic Job Candidate Search Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions Inherent Explainability Pattern Theory-based Video Event Interpretations 299 pp. Englisch.
Langue : anglais
Edité par Springer International Publishing AG, Cham, 2019
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-UnisGrand Eagle Retail
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 192,19
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Book & Merchandise. Etat : new. Book & Merchandise. This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with…almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: Evaluation and Generalization in Interpretable Machine Learning Explanation Methods in Deep Learning Learning Functional Causal Models with Generative Neural Networks Learning Interpreatable Rules for Multi-Label Classification Structuring Neural Networks for More Explainable Predictions Generating Post Hoc Rationales of Deep Visual Classification Decisions Ensembling Visual Explanations Explainable Deep Driving by Visualizing Causal Attention Interdisciplinary Perspective on Algorithmic Job Candidate Search Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions Inherent Explainability Pattern Theory-based Video Event Interpretations Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Langue : anglais
Edité par Springer-Verlag Gmbh Sep 2018, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Wegmann1855, Zwiesel, AllemagneWegmann1855
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 160,49
EUR 25,95 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Bündel. Etat : Neu. Neuware -This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.
Langue : anglais
Edité par Springer International Publishing AG, CH, 2019
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-UniRarewaves.com USA
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 194,62
Frais de port gratuitsExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Mixed Media Product. Etat : New. 2018 ed. This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost hum…an-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning· Explanation Methods in Deep Learning· Learning Functional Causal Models with Generative Neural Networks· Learning Interpreatable Rules for Multi-Label Classification· Structuring Neural Networks for More Explainable Predictions· Generating Post Hoc Rationales of Deep Visual Classification Decisions· Ensembling Visual Explanations· Explainable Deep Driving by Visualizing Causal Attention· Interdisciplinary Perspective on Algorithmic Job Candidate Search· Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations.
Langue : anglais
Edité par Springer-Verlag New York Inc, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture souple
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 178,42
EUR 14,70 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Paperback. Etat : Brand New. pap/psc edition. 299 pages. 9.25x6.10x0.79 inches. In Stock.
Langue : anglais
Edité par Springer-Verlag Gmbh Sep 2018, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagnebuchversandmimpf2000
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 160,49
EUR 60,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Bündel. Etat : Neu. Neuware -This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 299 pp. Englisch.
Langue : anglais
Edité par Springer-Verlag Gmbh Sep 2018, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 160,49
EUR 63,37 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 1 disponible(s)
Kombiprodukt. Etat : Neu. Neuware - This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-lik…e performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made what in the model structure explains its functioning Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: Evaluation and Generalization in Interpretable Machine Learning Explanation Methods in Deep Learning Learning Functional Causal Models with Generative Neural Networks Learning Interpreatable Rules for Multi-Label Classification Structuring Neural Networks for More Explainable Predictions Generating Post Hoc Rationales of Deep Visual Classification Decisions Ensembling Visual Explanations Explainable Deep Driving by Visualizing Causal Attention Interdisciplinary Perspective on Algorithmic Job Candidate Search Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions Inherent Explainability Pattern Theory-based Video Event Interpretations.
Langue : anglais
Edité par Springer-Verlag New York Inc, 2018
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture souple
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 238,26
EUR 14,70 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Paperback. Etat : Brand New. pap/psc edition. 299 pages. 9.25x6.10x0.79 inches. In Stock.
Langue : anglais
Edité par Springer International Publishing AG, CH, 2019
Série : The Springer Series on Challenges in Machine Learning, Livre 4 sur 8. Livre 4 sur 8 - The Springer Series on Challenges in Machine Learning
- Couverture rigide
Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 184,13
EUR 76,43 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Mixed Media Product. Etat : New. 2018 ed. This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning.Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost hum…an-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning· Explanation Methods in Deep Learning· Learning Functional Causal Models with Generative Neural Networks· Learning Interpreatable Rules for Multi-Label Classification· Structuring Neural Networks for More Explainable Predictions· Generating Post Hoc Rationales of Deep Visual Classification Decisions· Ensembling Visual Explanations· Explainable Deep Driving by Visualizing Causal Attention· Interdisciplinary Perspective on Algorithmic Job Candidate Search· Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations.
