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Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models
Seller: Bay State Book Company, North Smithfield, RI, U.S.A.
Seller rating 5 out of 5 stars
Condition: good. The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.
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Paperback. Condition: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
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Explainable AI Solutions: Creating Transparent and Trustworthy Machine Learning Models
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 26.62
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paperback. Condition: Very good condition. very clean,fast ship.
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Explainable and Interpretable Models in Computer Vision and Machine Learning.
Book 4 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
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: Englisch.
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Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more (Paperback or Softback)
Language: English
Published by Packt Publishing 7/29/2022, 2022
ISBN 10: 1803246154 ISBN 13: 9781803246154
Paperback or Softback. Condition: New. Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more. Book.
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Condition: As New. Unread book in perfect condition.
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Interpretable Machine Learning with Python - Second Edition: Build explainable, fair, and robust high-performance models with hands-on, real-world exa (Paperback or Softback)
Language: English
Published by Packt Publishing 10/31/2023, 2023
ISBN 10: 180323542X ISBN 13: 9781803235424
Paperback or Softback. Condition: New. Interpretable Machine Learning with Python - Second Edition: Build explainable, fair, and robust high-performance models with hands-on, real-world exa. Book.
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Condition: As New. Unread book in perfect condition.
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Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 55.11
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Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 53.81
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Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 55.09
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Applied Machine Learning Explainability Techniques: Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more
Language: English
Published by Packt Publishing 2022-07-29, 2022
ISBN 10: 1803246154 ISBN 13: 9781803246154
US$ 55.35
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Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 60.82
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Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 60.82
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Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 60.80
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Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 67.10
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Meaningful Machine Learning: A Guide for Making Models Explainable
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200102414 ISBN 13: 9786200102416
Condition: New.
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Explainable and Interpretable Models in Computer Vision and Machine Learning (The Springer Series on Challenges in Machine Learning)
Book 4 of 8: The Springer Series on Challenges in Machine LearningSeller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Gebundene Ausgabe. Condition: 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 vision and machine learning.Springer Fachmedien Wiesbaden GmbH, Abraham-Lincoln-Str. 46, 65189 Wiesbaden 316 pp. Englisch.
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Taschenbuch. Condition: Neu. Explainable Graph Neural Networks for Fraud Detection | Integrating XAI into Graph-Based Machine Learning Models for Financial Security | Thaer Alkassab | Taschenbuch | Englisch | 2025 | GlobeEdit | EAN 9786137806364 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Explainable and Interpretable Models in Computer Vision and Machine Learning
Book 4 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer International Publishing, 2019
ISBN 10: 3319981307 ISBN 13: 9783319981307
Condition: 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.
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Meaningful Machine Learning | A Guide for Making Models Explainable
Language: English
Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200102414 ISBN 13: 9786200102416
Taschenbuch. Condition: Neu. Meaningful Machine Learning | A Guide for Making Models Explainable | Binit Patel | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786200102416 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Explainable and Interpretable Models in Computer Vision and Machine Learning
Book 4 of 8: The Springer Series on Challenges in Machine LearningLanguage: English
Published by Springer-Verlag GmbH, 2018
ISBN 10: 3319981307 ISBN 13: 9783319981307
Condition: 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.
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Explainable Machine Learning Models and Architectures (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 2023
ISBN 10: 1394185847 ISBN 13: 9781394185849
Hardcover. Condition: new. Hardcover. EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
