Explainable interpretable models computer (12 Ergebnisse)
Sprache: Englisch
Verlag: Cham, Springer. 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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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.
Sprache: Englisch
Verlag: Springer 2019
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschlandbuchversandmimpf2000
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Gebundene Ausgabe. Zustand: 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 vis…ion and machine learning.Springer Fachmedien Wiesbaden GmbH, Abraham-Lincoln-Str. 46, 65189 Wiesbaden 316 pp. Englisch.
Sprache: Englisch
Verlag: Springer International Publishing 2019
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Zustand: 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.
Sprache: Englisch
Verlag: Springer-Verlag GmbH 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Zustand: 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… 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.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Sep 2018 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Softcover
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Taschenbuch. Zustand: 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 299 pp. Englisch.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Sep 2018 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Softcover
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Taschenbuch. Zustand: 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 299 pp. Englisch.
Sprache: Englisch
Verlag: Springer International Publishing AG, Cham 2019
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Book & Merchandise. Zustand: 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 wit…h 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.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Sep 2018 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Bündel. Zustand: 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.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Sep 2018 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Bündel. Zustand: 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.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Sep 2018 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Kombiprodukt. Zustand: 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-l…ike 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.
Sprache: Englisch
Verlag: Springer-Verlag GmbH 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Hardcover
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Zustand: gut. 2018. Explainable and Interpretable Models in Computer Vision and Machine Learning In deutscher Sprache. pages.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc 2018
Serie: The Springer Series on Challenges in Machine Learning, Buch 4 von 8. Buch 4 von 8 - The Springer Series on Challenges in Machine Learning
- Softcover
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Paperback. Zustand: Brand New. pap/psc edition. 299 pages. 9.25x6.10x0.79 inches. In Stock.
