Real Time Applications Machine Learning (59 results)
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Hardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
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- Hardcover
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from dataset…s of UCI repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, time-series analysis, gene-expression data classification.
Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
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- Softcover
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- Softcover
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Taschenbuch. Condition: Neu. Improving Classifier Generalization | Real-Time Machine Learning based Applications | Rahul Kumar Sevakula (u. a.) | Taschenbuch | xxiii | Englisch | 2023 | Springer | EAN 9789811950759 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartman…n[at]springer[dot]com | Anbieter: preigu.
- Hardcover
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Machine Learning and Deep Learning in Real-Time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Softcover
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- Softcover
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Machine Learning and Deep Learning in Real-Time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Softcover
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Softcover
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Softcover
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Machine Learning and Deep Learning in Real-Time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Softcover
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- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 148.41
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI… repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, time-series analysis, gene-expression data classification.
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 147.96
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches. The contents highlight methods to improve classification performance in numerous case studies: ranging from datasets of UCI reposi…tory to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, time-series analysis, gene-expression data classification.
Machine Learning and Deep Learning in Real-Time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Softcover
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- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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£ 199.23
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Hardcover. Condition: Brand New. 189 pages. 9.25x6.10x0.63 inches. In Stock.
- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal Kant (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Hardcover
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- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
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Machine Learning and Deep Learning in Real-time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Hardcover
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Machine Learning and Deep Learning in Real-time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Hardcover
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal Kant (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Hardcover
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Real-time Applications of Machine Learning in Cyber-physical Systems
Easwaran, Balamurugan (EDT); Hiran, Kamal Kant (EDT); Krishnan, Sangeetha (EDT); Doshi, Ruchi (EDT)
- Hardcover
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Machine Learning and Deep Learning in Real-time Applications
Mahrishi, Mehul (EDT); Hiran, Kamal Kant (EDT); Meena, Gaurav (EDT); Sharma, Paawan (EDT)
- Hardcover
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- Softcover
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