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41.
Подробнее
S 17
Salcedo, Jesus.
Machine Learning for Data Mining [[electronic resource] :] : Improve Your Data Mining Capabilities with Advanced Predictive Modeling. / Jesus. Salcedo. - Birmingham : : Packt Publishing, Limited,, 2019. - 1 online resource (247 p.). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/DB31EBDC-325D-4F42-81DF-F1B237EA3081. - ISBN 1838821554 (electronic bk.). - ISBN 9781838821555 (electronic bk.)
Description based upon print version of record.
Параллельные издания: Print version: : Salcedo, Jesus Machine Learning for Data Mining : Improve Your Data Mining Capabilities with Advanced Predictive Modeling. - Birmingham : Packt Publishing, Limited,c2019. - ISBN 9781838828974
~РУБ DDC 006.312
Рубрики: Data mining.
Machine learning.
Artificial intelligence.
Аннотация: Most data mining opportunities involve machine learning and often come with greater financial rewards. This book will help you bring the power of machine learning techniques into your data mining work. By the end of the book, you will be able to create accurate predictive models for data mining.
S 17
Salcedo, Jesus.
Machine Learning for Data Mining [[electronic resource] :] : Improve Your Data Mining Capabilities with Advanced Predictive Modeling. / Jesus. Salcedo. - Birmingham : : Packt Publishing, Limited,, 2019. - 1 online resource (247 p.). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/DB31EBDC-325D-4F42-81DF-F1B237EA3081. - ISBN 1838821554 (electronic bk.). - ISBN 9781838821555 (electronic bk.)
Description based upon print version of record.
Параллельные издания: Print version: : Salcedo, Jesus Machine Learning for Data Mining : Improve Your Data Mining Capabilities with Advanced Predictive Modeling. - Birmingham : Packt Publishing, Limited,c2019. - ISBN 9781838828974
Рубрики: Data mining.
Machine learning.
Artificial intelligence.
Аннотация: Most data mining opportunities involve machine learning and often come with greater financial rewards. This book will help you bring the power of machine learning techniques into your data mining work. By the end of the book, you will be able to create accurate predictive models for data mining.
42.
Подробнее
D 29
De Marchi, Marchi, Leonardo.
Hands-on neural networks : : learn how to build and train your first neural network model using Python / / Leonardo De Marchi, Laura Mitchell. - Birmingham, UK : : Packt Publishing,, 2019. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/1DF618BF-0F92-4263-B417-14EC536EE7B5. - ISBN 1788999886 (electronic bk.). - ISBN 9781788999885 (electronic bk.)
~РУБ DDC 006.32
Рубрики: Neural networks (Computer science)
Python (Computer program language)
Artificial intelligence.
Artificial intelligence.
Neural networks (Computer science)
Python (Computer program language)
Аннотация: This book will be a journey for beginners who want to step into the world of deep learning and artificial intelligence. It will thoughtfully take you through the training and implementation of various neural network architectures using the Python ecosystem. You will master each neural network architecture while understanding its working mechanism.
Доп.точки доступа:
Mitchell, Laura.
D 29
De Marchi, Marchi, Leonardo.
Hands-on neural networks : : learn how to build and train your first neural network model using Python / / Leonardo De Marchi, Laura Mitchell. - Birmingham, UK : : Packt Publishing,, 2019. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/1DF618BF-0F92-4263-B417-14EC536EE7B5. - ISBN 1788999886 (electronic bk.). - ISBN 9781788999885 (electronic bk.)
Рубрики: Neural networks (Computer science)
Python (Computer program language)
Artificial intelligence.
Artificial intelligence.
Neural networks (Computer science)
Python (Computer program language)
Аннотация: This book will be a journey for beginners who want to step into the world of deep learning and artificial intelligence. It will thoughtfully take you through the training and implementation of various neural network architectures using the Python ecosystem. You will master each neural network architecture while understanding its working mechanism.
Доп.точки доступа:
Mitchell, Laura.
43.
Подробнее
A 28
AI and big data's potential for disruptive innovation / / Moses Strydom and Sheryl Buckley, editors. - 4018/978-1-5225-9687-5. - Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : : IGI Global,, [2020]. - 1 online resource (23 PDFs (405 pages)) ( час. мин.), 4018/978-1-5225-9687-5. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/783923B9-37EC-441D-AB35-371BBC8DC365. - ISBN 9781522596899 (ebook). - ISBN 1522596895. - ISBN 9781522596905 (electronic bk.). - ISBN 1522596909 (electronic bk.)
Description based on title screen (IGI Global, viewed 09/04/2019).
Параллельные издания: Print version: :
Содержание:
Chapter 1. Big data intelligence and perspectives in darwinian disruption -- Chapter 2. Ontology-based open tourism data integration framework: trip planning platform -- Chapter 3. Artificial intelligence for extended software robots, applications, algorithms, and simulators -- Chapter 4. Machine learning and artificial intelligence: rural development analysis using satellite image processing -- Chapter 5. Wearables, artificial intelligence, and the future of healthcare -- Chapter 6. Blockchain as a disruptive technology: architecture, business scenarios, and future trends -- Chapter 7. Disrupting agriculture: the status and prospects for AI and big data in smart agriculture -- Chapter 8. Automated grading of tomatoes using artificial intelligence: the case of Zimbabwe -- Chapter 9. Applications of big data and AI in electric power systems engineering -- Chapter 10. Blockchain and its integration as a disruptive technology -- Chapter 11. Cyber secure man-in-the-middle attack intrusion detection using machine learning algorithms -- Chapter 12. The intersection of data analytics and data-driven innovation.
~РУБ DDC 338/.064
Рубрики: Artificial intelligence--Industrial applications.
Big data--Industrial applications.
Disruptive technologies.
Artificial intelligence--Industrial applications.
Disruptive technologies.
Аннотация: "This book examines the disruptive technological advances involving artificial intelligence and big data"--
Доп.точки доступа:
Strydom, Moses, (1944-) \editor.\
Buckley, Sheryl, (1959-) \editor.\
IGI Global,
A 28
AI and big data's potential for disruptive innovation / / Moses Strydom and Sheryl Buckley, editors. - 4018/978-1-5225-9687-5. - Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) : : IGI Global,, [2020]. - 1 online resource (23 PDFs (405 pages)) ( час. мин.), 4018/978-1-5225-9687-5. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/783923B9-37EC-441D-AB35-371BBC8DC365. - ISBN 9781522596899 (ebook). - ISBN 1522596895. - ISBN 9781522596905 (electronic bk.). - ISBN 1522596909 (electronic bk.)
Description based on title screen (IGI Global, viewed 09/04/2019).
Параллельные издания: Print version: :
Содержание:
Chapter 1. Big data intelligence and perspectives in darwinian disruption -- Chapter 2. Ontology-based open tourism data integration framework: trip planning platform -- Chapter 3. Artificial intelligence for extended software robots, applications, algorithms, and simulators -- Chapter 4. Machine learning and artificial intelligence: rural development analysis using satellite image processing -- Chapter 5. Wearables, artificial intelligence, and the future of healthcare -- Chapter 6. Blockchain as a disruptive technology: architecture, business scenarios, and future trends -- Chapter 7. Disrupting agriculture: the status and prospects for AI and big data in smart agriculture -- Chapter 8. Automated grading of tomatoes using artificial intelligence: the case of Zimbabwe -- Chapter 9. Applications of big data and AI in electric power systems engineering -- Chapter 10. Blockchain and its integration as a disruptive technology -- Chapter 11. Cyber secure man-in-the-middle attack intrusion detection using machine learning algorithms -- Chapter 12. The intersection of data analytics and data-driven innovation.
Рубрики: Artificial intelligence--Industrial applications.
Big data--Industrial applications.
Disruptive technologies.
Artificial intelligence--Industrial applications.
Disruptive technologies.
Аннотация: "This book examines the disruptive technological advances involving artificial intelligence and big data"--
Доп.точки доступа:
Strydom, Moses, (1944-) \editor.\
Buckley, Sheryl, (1959-) \editor.\
IGI Global,
44.
Подробнее
B 40
Bekdaş, Gebrail.
Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering / Gebrail. Bekdaş, Nigdeli, Sinan Melih., Yücel, Melda. - Hershey : : IGI Global,, 2019. - 1 online resource (327 pages). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D40641E1-9BF1-4C36-A4FC-3BA75D00E247. - ISBN 179980304X. - ISBN 9781799803041 (electronic bk.)
Print version record.
Параллельные издания: Print version: : Bekdaş, Gebrail. Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering. - Hershey : IGI Global, ©2019. - ISBN 9781799803010
Содержание:
Title Page; Copyright Page; Book Series; Table of Contents; Detailed Table of Contents; Preface; Chapter 1: Review and Applications of Machine Learning and Artificial Intelligence in Engineering; Chapter 2: Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems; Chapter 3: A Novel Prediction Perspective to the Bending Over Sheave Fatigue Lifetime of Steel Wire Ropes by Means of Artificial Neural Networks; Chapter 4: Introduction and Application Aspects of Machine Learning for Model Reference Adaptive Control With Polynomial Neurons
Chapter 5: Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning MethodsChapter 6: A Scientometric Analysis and a Review on Current Literature of Computer Vision Applications; Chapter 7: High Performance Concrete (HPC) Compressive Strength Prediction With Advanced Machine Learning Methods; Chapter 8: Artificial Intelligence Towards Water Conservation; Chapter 9: Analysis of Ground Water Quality Using Statistical Techniques; Chapter 10: Probe People and Vehicle-Based Data Sources Application in Smart Transportation
Chapter 11: Application of Machine Learning Methods for Passenger Demand Prediction in Transfer Stations of Istanbul's Public Transportation SystemChapter 12: Metaheuristics Approaches to Solve the Employee Bus Routing Problem With Clustering-Based Bus Stop Selection; Chapter 13: An Assessment of Imbalanced Control Chart Pattern Recognition by Artificial Neural Networks; Chapter 14: An Exploration of Machine Learning Methods for Biometric Identification Based on Keystroke Dynamics; Compilation of References; About the Contributors; Index
~РУБ DDC 620.00285/63
Рубрики: Artificial intelligence.
Civil engineering--Data processing.
Machine learning.
Mechanical engineering--Data processing.
Industrial engineering--Data processing.
Аннотация: In today's developing world, industries are constantly required to improve and advance. New approaches are being implemented to determine optimum values and solutions for models such as artificial intelligence and machine learning. Research is a necessity for determining how these recent methods are being applied within the engineering field and what effective solutions they are providing. Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering is a collection of innovative research on the methods and implementation of machine learning and AI.
Доп.точки доступа:
Nigdeli, Sinan Melih.
Yücel, Melda.
B 40
Bekdaş, Gebrail.
Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering / Gebrail. Bekdaş, Nigdeli, Sinan Melih., Yücel, Melda. - Hershey : : IGI Global,, 2019. - 1 online resource (327 pages). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D40641E1-9BF1-4C36-A4FC-3BA75D00E247. - ISBN 179980304X. - ISBN 9781799803041 (electronic bk.)
Print version record.
Параллельные издания: Print version: : Bekdaş, Gebrail. Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering. - Hershey : IGI Global, ©2019. - ISBN 9781799803010
Содержание:
Title Page; Copyright Page; Book Series; Table of Contents; Detailed Table of Contents; Preface; Chapter 1: Review and Applications of Machine Learning and Artificial Intelligence in Engineering; Chapter 2: Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems; Chapter 3: A Novel Prediction Perspective to the Bending Over Sheave Fatigue Lifetime of Steel Wire Ropes by Means of Artificial Neural Networks; Chapter 4: Introduction and Application Aspects of Machine Learning for Model Reference Adaptive Control With Polynomial Neurons
Chapter 5: Optimum Design of Carbon Fiber-Reinforced Polymer (CFRP) Beams for Shear Capacity via Machine Learning MethodsChapter 6: A Scientometric Analysis and a Review on Current Literature of Computer Vision Applications; Chapter 7: High Performance Concrete (HPC) Compressive Strength Prediction With Advanced Machine Learning Methods; Chapter 8: Artificial Intelligence Towards Water Conservation; Chapter 9: Analysis of Ground Water Quality Using Statistical Techniques; Chapter 10: Probe People and Vehicle-Based Data Sources Application in Smart Transportation
Chapter 11: Application of Machine Learning Methods for Passenger Demand Prediction in Transfer Stations of Istanbul's Public Transportation SystemChapter 12: Metaheuristics Approaches to Solve the Employee Bus Routing Problem With Clustering-Based Bus Stop Selection; Chapter 13: An Assessment of Imbalanced Control Chart Pattern Recognition by Artificial Neural Networks; Chapter 14: An Exploration of Machine Learning Methods for Biometric Identification Based on Keystroke Dynamics; Compilation of References; About the Contributors; Index
Рубрики: Artificial intelligence.
Civil engineering--Data processing.
Machine learning.
Mechanical engineering--Data processing.
Industrial engineering--Data processing.
Аннотация: In today's developing world, industries are constantly required to improve and advance. New approaches are being implemented to determine optimum values and solutions for models such as artificial intelligence and machine learning. Research is a necessity for determining how these recent methods are being applied within the engineering field and what effective solutions they are providing. Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering is a collection of innovative research on the methods and implementation of machine learning and AI.
Доп.точки доступа:
Nigdeli, Sinan Melih.
Yücel, Melda.
45.
Подробнее
A 28
AI techniques for reliability prediction for electronic components / / [edited by] Cherry Bhargava. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2020]. - 1 online resource (xv, 330 pages). : il. - (Advances in Computational Intelligence and Robotics (ACIR) Book Series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/C93787D2-D836-4843-93BF-213ED894EE03. - ISBN 1799814661 (electronic book). - ISBN 9781799814665 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 02, 2019).
Параллельные издания: Print version: : AI techniques for reliability prediction for electronic components. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, 2020. - ISBN 9781799814641
Содержание:
Residual life estimation of humidity sensor DHT11 using ANN / Pardeep Sharma, Lovely Professional University, India, Cherry Bhargava, Lovely Professional University, India, Shivani Gulati, Lambton College, Canada -- Frequency based RO-PUF / Abhishek Kumar, Lovely Professional University, India, Jyotirmoy Pathak, Lovely Professional University, India, Suman Tripathi, Lovely Professional University, India -- Modelling analysis and simulation for reliability prediction for thermal power system / Vikram Kamboj, Lovely Professional University, India.
~РУБ DDC 621.38150285/63
Рубрики: Electronic apparatus and appliances--Reliability.
Electronic apparatus and appliances--Testing--Data processing.
Electronic apparatus and appliances--Service life.
Artificial intelligence--Industrial applications.
Artificial intelligence--Industrial applications.
Electronic apparatus and appliances--Reliability.
Electronic apparatus and appliances--Testing--Data processing.
Аннотация: "This book explores the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field"--
Доп.точки доступа:
Bhargava, Cherry, (1982-) \editor.\
A 28
AI techniques for reliability prediction for electronic components / / [edited by] Cherry Bhargava. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2020]. - 1 online resource (xv, 330 pages). : il. - (Advances in Computational Intelligence and Robotics (ACIR) Book Series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/C93787D2-D836-4843-93BF-213ED894EE03. - ISBN 1799814661 (electronic book). - ISBN 9781799814665 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 02, 2019).
Параллельные издания: Print version: : AI techniques for reliability prediction for electronic components. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, 2020. - ISBN 9781799814641
Содержание:
Residual life estimation of humidity sensor DHT11 using ANN / Pardeep Sharma, Lovely Professional University, India, Cherry Bhargava, Lovely Professional University, India, Shivani Gulati, Lambton College, Canada -- Frequency based RO-PUF / Abhishek Kumar, Lovely Professional University, India, Jyotirmoy Pathak, Lovely Professional University, India, Suman Tripathi, Lovely Professional University, India -- Modelling analysis and simulation for reliability prediction for thermal power system / Vikram Kamboj, Lovely Professional University, India.
Рубрики: Electronic apparatus and appliances--Reliability.
Electronic apparatus and appliances--Testing--Data processing.
Electronic apparatus and appliances--Service life.
Artificial intelligence--Industrial applications.
Artificial intelligence--Industrial applications.
Electronic apparatus and appliances--Reliability.
Electronic apparatus and appliances--Testing--Data processing.
Аннотация: "This book explores the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field"--
Доп.точки доступа:
Bhargava, Cherry, (1982-) \editor.\
46.
Подробнее
A 95
Avatar-based control, estimation, communications, and development of neuron multi-functional technology platforms / / Vardan Mkrttchian, Ekaterina Aleshina, Leyla Gamidullaeva (editors). - Hershey, PA : : Engineering Science Reference (an imprint of IGI Global),, [2020]. - 1 online resource (xxvii, 355 pages). : il. - (Advances in computational intelligence and robotics (ACIR) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/C9B64DC7-3986-4E3E-9C81-71111D10E9A6. - ISBN 1799815838 (electronic book). - ISBN 9781799815839 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 20, 2019).
Параллельные издания: Print version: : Avatar-based control, estimation, communications, and development of neuron multi-functional technology platforms. - Hershey, PA : Engineering Science Reference, [2020]. - ISBN 9781799815815
~РУБ DDC 006.8
Рубрики: Avatars (Virtual reality)
Artificial intelligence.
Information technology--Social aspects.
Shared virtual environments.
Artificial intelligence.
Avatars (Virtual reality)
Information technology--Social aspects.
Shared virtual environments.
Аннотация: "This book presents techniques, case studies, and methodologies that combine the use of intelligent artificial and natural approaches with optimization techniques for facing problems and combines many types of hardware and software with a variety of communication technologies to enable the development of innovative applications"--
Доп.точки доступа:
Mkrttchian, Vardan, (1950-) \editor.\
Aleshina, Ekaterina, (1978-) \editor.\
Gamidullaeva, Leyla, (1985-) \editor.\
A 95
Avatar-based control, estimation, communications, and development of neuron multi-functional technology platforms / / Vardan Mkrttchian, Ekaterina Aleshina, Leyla Gamidullaeva (editors). - Hershey, PA : : Engineering Science Reference (an imprint of IGI Global),, [2020]. - 1 online resource (xxvii, 355 pages). : il. - (Advances in computational intelligence and robotics (ACIR) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/C9B64DC7-3986-4E3E-9C81-71111D10E9A6. - ISBN 1799815838 (electronic book). - ISBN 9781799815839 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 20, 2019).
Параллельные издания: Print version: : Avatar-based control, estimation, communications, and development of neuron multi-functional technology platforms. - Hershey, PA : Engineering Science Reference, [2020]. - ISBN 9781799815815
Рубрики: Avatars (Virtual reality)
Artificial intelligence.
Information technology--Social aspects.
Shared virtual environments.
Artificial intelligence.
Avatars (Virtual reality)
Information technology--Social aspects.
Shared virtual environments.
Аннотация: "This book presents techniques, case studies, and methodologies that combine the use of intelligent artificial and natural approaches with optimization techniques for facing problems and combines many types of hardware and software with a variety of communication technologies to enable the development of innovative applications"--
Доп.точки доступа:
Mkrttchian, Vardan, (1950-) \editor.\
Aleshina, Ekaterina, (1978-) \editor.\
Gamidullaeva, Leyla, (1985-) \editor.\
47.
Подробнее
L 24
Lanham, Micheal,.
Hands-on reinforcement learning for games : : implementing self-learning agents in games using artificial intelligence techniques / / Micheal Lanham. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/794FA818-3BC4-4505-8A70-925376C4C725. - ISBN 9781839216770. - ISBN 1839216778
Description based on online resource; title from title page (Safari, viewed June 17, 2020).
Параллельные издания: Print version: : Lanham, Micheal. Hands-On Reinforcement Learning for Games : Implementing Self-Learning Agents in Games Using Artificial Intelligence Techniques. - Birmingham : Packt Publishing, Limited, ©2020. - ISBN 9781839214936
~РУБ DDC 794.81631
Рубрики: Machine learning.
Artificial intelligence.
Reinforcement learning.
Computer games--Programming.
Application software--Development.
Computer games--Programming.
Аннотация: The AI revolution is here and it is embracing games. Game developers are being challenged to enlist cutting edge AI as part of their games. In this book, you will look at the journey of building capable AI using reinforcement learning algorithms and techniques. You will learn to solve complex tasks and build next-generation games using a ...
L 24
Lanham, Micheal,.
Hands-on reinforcement learning for games : : implementing self-learning agents in games using artificial intelligence techniques / / Micheal Lanham. - Birmingham, UK : : Packt Publishing,, 2020. - 1 online resource (1 volume) : : il. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/794FA818-3BC4-4505-8A70-925376C4C725. - ISBN 9781839216770. - ISBN 1839216778
Description based on online resource; title from title page (Safari, viewed June 17, 2020).
Параллельные издания: Print version: : Lanham, Micheal. Hands-On Reinforcement Learning for Games : Implementing Self-Learning Agents in Games Using Artificial Intelligence Techniques. - Birmingham : Packt Publishing, Limited, ©2020. - ISBN 9781839214936
Рубрики: Machine learning.
Artificial intelligence.
Reinforcement learning.
Computer games--Programming.
Application software--Development.
Computer games--Programming.
Аннотация: The AI revolution is here and it is embracing games. Game developers are being challenged to enlist cutting edge AI as part of their games. In this book, you will look at the journey of building capable AI using reinforcement learning algorithms and techniques. You will learn to solve complex tasks and build next-generation games using a ...
48.
Подробнее
D 30
Deep Learning : : Research and Applications / / edited by Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy. - 1515/9783110670905. - Berlin ; ; Boston : : De Gruyter,, ©2020. - 1 online resource (IX, 152 p.). ( час. мин.), 1515/9783110670905. - (De Gruyter Frontiers in Computational Intelligence ; ; volume 7). - In English. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/A6744D2D-9D62-4B48-93ED-B318614EC4E0. - ISBN 9783110670929 (electronic bk.). - ISBN 3110670925 (electronic bk.). - ISBN 9783110670905 (electronic book). - ISBN 3110670909 (electronic book)
Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020).
Параллельные издания:
1.
2.
~РУБ DDC 006.3/1
Рубрики: Machine learning.
Artificial intelligence--Industrial applications.
Algorithmus.
Deep Learning.
Maschinelles Lernen.
Neuronales Netz.
COMPUTERS / Intelligence (AI) & Semantics.
Artificial intelligence--Industrial applications
Machine learning
Аннотация: This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
Доп.точки доступа:
Bhattacharyya, Siddhartha, \ed.\
Ella Hassanien, Aboul, \ed.\
Saha, Satadal, \ed.\
Snasel, Vaclav, \ed.\
Tripathy, B. K., \ed.\
D 30
Deep Learning : : Research and Applications / / edited by Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy. - 1515/9783110670905. - Berlin ; ; Boston : : De Gruyter,, ©2020. - 1 online resource (IX, 152 p.). ( час. мин.), 1515/9783110670905. - (De Gruyter Frontiers in Computational Intelligence ; ; volume 7). - In English. - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/A6744D2D-9D62-4B48-93ED-B318614EC4E0. - ISBN 9783110670929 (electronic bk.). - ISBN 3110670925 (electronic bk.). - ISBN 9783110670905 (electronic book). - ISBN 3110670909 (electronic book)
Description based on online resource; title from PDF title page (publisher's Web site, viewed 23. Jun 2020).
Параллельные издания:
1.
2.
Рубрики: Machine learning.
Artificial intelligence--Industrial applications.
Algorithmus.
Deep Learning.
Maschinelles Lernen.
Neuronales Netz.
COMPUTERS / Intelligence (AI) & Semantics.
Artificial intelligence--Industrial applications
Machine learning
Аннотация: This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.
Доп.точки доступа:
Bhattacharyya, Siddhartha, \ed.\
Ella Hassanien, Aboul, \ed.\
Saha, Satadal, \ed.\
Snasel, Vaclav, \ed.\
Tripathy, B. K., \ed.\
49.
Подробнее
H 22
HANDBOOK OF RESEARCH ON APPLIED AI FOR INTERNATIONAL BUSINESS AND MARKETING APPLICATIONS [[electronic resource].]. - [Б. м.] : BUSINESS SCIENCE REFERENC,, 2020. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/77CECFDC-F13A-421E-888E-F033367D1BA7. - ISBN 9781799850793 (electronic bk.). - ISBN 179985079X (electronic bk.)
Параллельные издания: Print version: :
Содержание:
Title Page -- Copyright Page -- Book Series -- Editorial Advisory Board -- List of Contributors -- Table of Contents -- Detailed Table of Contents -- Foreword -- Preface -- Chapter 1: Artificial Intelligence, Marketing, and the Fourth Industrial Revolution -- Chapter 2: New Marketing Strategy -- Chapter 3: Reinforcement Learning in Social Media Marketing -- Chapter 4: Importance of Applying Big Data Concept in Marketing Decision Making -- Chapter 5: Marketing and Artificial Intelligence -- Chapter 6: The Impact of AI on Disintermediation Processes in the Tourism Industry
Chapter 7: Governing by Humans, Not by Robots -- Chapter 8: Economic AI Literacy -- Chapter 9: Finance in the World of Artificial Intelligence and Digitalization -- Chapter 10: Fuzzy Logic in Portfolio Selection -- Chapter 11: Business Intelligence -- Chapter 12: Artificial Intelligence and Supply Chain Management Application, Development, and Forecast -- Chapter 13: Artificial Intelligence and Backshoring Strategies -- Chapter 14: Bargaining Chip
Chapter 15: Finding the Solution of Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems by Using Different Methods With Some Software Packages -- Chapter 16: Use of Finite Markov Chains in Business Problems Involving Decision Making and Case-Based Reasoning -- Chapter 17: Risk Management in the Oil and Gas Industry Related to the AI Tools -- Chapter 18: Non-Invasive Personalized In-Store Location-Based Marketing -- Chapter 19: Modeling Sovereign Rating of India -- Chapter 20: Study on Indian Stock Market Performance Based on Commodities
Chapter 21: The Impact of Augmented Reality Experiential Marketing on Tourist Experience Satisfaction -- Chapter 22: Convolutional Neural Networks for Real-Time Eye Tracking in Interactive Applications -- Chapter 23: Determining the Motives and Behaviors of Brand Hate -- Chapter 24: Evaluation of LPI Values of Transition Economies Countries With a Grey MCDM Model -- Chapter 25: Extremely Fast Heuristic Event-Driven Job Shop Scheduler With a New Class of Extended Petri Nets -- Chapter 26: Artificial Intelligence Applications in Accounting and Financial Reporting Systems
Chapter 27: A Research on Hedonic and Utilitarian Consumption Behavior of Young Consumers on Big Discount Days -- Chapter 28: Credit Scoring -- Compilation of References -- About the Contributors -- Index
~РУБ DDC 658/.0563
Рубрики: Automation--Management.
Technological innovations--Management.
Artificial intelligence--Industrial applications.
Аннотация: Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical s.
H 22
HANDBOOK OF RESEARCH ON APPLIED AI FOR INTERNATIONAL BUSINESS AND MARKETING APPLICATIONS [[electronic resource].]. - [Б. м.] : BUSINESS SCIENCE REFERENC,, 2020. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/77CECFDC-F13A-421E-888E-F033367D1BA7. - ISBN 9781799850793 (electronic bk.). - ISBN 179985079X (electronic bk.)
Параллельные издания: Print version: :
Содержание:
Title Page -- Copyright Page -- Book Series -- Editorial Advisory Board -- List of Contributors -- Table of Contents -- Detailed Table of Contents -- Foreword -- Preface -- Chapter 1: Artificial Intelligence, Marketing, and the Fourth Industrial Revolution -- Chapter 2: New Marketing Strategy -- Chapter 3: Reinforcement Learning in Social Media Marketing -- Chapter 4: Importance of Applying Big Data Concept in Marketing Decision Making -- Chapter 5: Marketing and Artificial Intelligence -- Chapter 6: The Impact of AI on Disintermediation Processes in the Tourism Industry
Chapter 7: Governing by Humans, Not by Robots -- Chapter 8: Economic AI Literacy -- Chapter 9: Finance in the World of Artificial Intelligence and Digitalization -- Chapter 10: Fuzzy Logic in Portfolio Selection -- Chapter 11: Business Intelligence -- Chapter 12: Artificial Intelligence and Supply Chain Management Application, Development, and Forecast -- Chapter 13: Artificial Intelligence and Backshoring Strategies -- Chapter 14: Bargaining Chip
Chapter 15: Finding the Solution of Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems by Using Different Methods With Some Software Packages -- Chapter 16: Use of Finite Markov Chains in Business Problems Involving Decision Making and Case-Based Reasoning -- Chapter 17: Risk Management in the Oil and Gas Industry Related to the AI Tools -- Chapter 18: Non-Invasive Personalized In-Store Location-Based Marketing -- Chapter 19: Modeling Sovereign Rating of India -- Chapter 20: Study on Indian Stock Market Performance Based on Commodities
Chapter 21: The Impact of Augmented Reality Experiential Marketing on Tourist Experience Satisfaction -- Chapter 22: Convolutional Neural Networks for Real-Time Eye Tracking in Interactive Applications -- Chapter 23: Determining the Motives and Behaviors of Brand Hate -- Chapter 24: Evaluation of LPI Values of Transition Economies Countries With a Grey MCDM Model -- Chapter 25: Extremely Fast Heuristic Event-Driven Job Shop Scheduler With a New Class of Extended Petri Nets -- Chapter 26: Artificial Intelligence Applications in Accounting and Financial Reporting Systems
Chapter 27: A Research on Hedonic and Utilitarian Consumption Behavior of Young Consumers on Big Discount Days -- Chapter 28: Credit Scoring -- Compilation of References -- About the Contributors -- Index
Рубрики: Automation--Management.
Technological innovations--Management.
Artificial intelligence--Industrial applications.
Аннотация: Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI for International Business and Marketing Applications is a critical s.
50.
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Advanced deep learning applications in big data analytics / / Hadj Ahmed Bouarara. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2021]. - 1 online resource. - (Advances in data mining and database management (ADMDM) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D71A6EE5-41D1-4E43-ADBB-209C649D2B2B. - ISBN 1799827933 (electronic book). - ISBN 9781799827931 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 07, 2020).
Параллельные издания: Print version: : Advanced deep learning applications in big data analytics. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]. - ISBN 9781799827917
Содержание:
Chapter 1. Advanced deep learning applications in big data analytics: introduction of Internet of things -- Chapter 2. Big data and cloud computing: a technological and literary background -- Chapter 3. Challenges and applications of data analytics in social perspectives: introduction of data science -- Chapter 4. Deep learning for social media text analytics -- Chapter 5. Deeplearning for computer vision problems: litterature review -- Chapter 6. Introduction of big data with analytics of big data -- Chapter 7. Machine learning in sentiment analysis over twitter: synthesis and comparative study -- Chapter 8. Machine learning techniques in spam detection -- Chapter 9. On swarm intelligence and its integration with Internet of things: challenges and applications -- Chapter 10. Physical characteristics of type 1 and 2 diabetic subjects: NCR, Indian-based computational perspective -- Chapter 11. Research information: bio-inspiration in information retrieval -- Chapter 12. Study on South Asian diabetic subjects on different attributes: a statistical approach.
~РУБ DDC 005.7
Рубрики: Big data.
Artificial intelligence.
Machine learning.
Artificial intelligence.
Big data.
Machine learning.
Аннотация: "This book explores the developing and application of deep learning in big data"--
Доп.точки доступа:
Bouarara, Hadj Ahmed, (1990-) \editor.\
A 22
Advanced deep learning applications in big data analytics / / Hadj Ahmed Bouarara. - Hershey, PA : : Engineering Science Reference, an imprint of IGI Global,, [2021]. - 1 online resource. - (Advances in data mining and database management (ADMDM) book series). - Includes bibliographical references and index. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/D71A6EE5-41D1-4E43-ADBB-209C649D2B2B. - ISBN 1799827933 (electronic book). - ISBN 9781799827931 (electronic bk.)
Description based on online resource; title from digital title page (viewed on December 07, 2020).
Параллельные издания: Print version: : Advanced deep learning applications in big data analytics. - Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]. - ISBN 9781799827917
Содержание:
Chapter 1. Advanced deep learning applications in big data analytics: introduction of Internet of things -- Chapter 2. Big data and cloud computing: a technological and literary background -- Chapter 3. Challenges and applications of data analytics in social perspectives: introduction of data science -- Chapter 4. Deep learning for social media text analytics -- Chapter 5. Deeplearning for computer vision problems: litterature review -- Chapter 6. Introduction of big data with analytics of big data -- Chapter 7. Machine learning in sentiment analysis over twitter: synthesis and comparative study -- Chapter 8. Machine learning techniques in spam detection -- Chapter 9. On swarm intelligence and its integration with Internet of things: challenges and applications -- Chapter 10. Physical characteristics of type 1 and 2 diabetic subjects: NCR, Indian-based computational perspective -- Chapter 11. Research information: bio-inspiration in information retrieval -- Chapter 12. Study on South Asian diabetic subjects on different attributes: a statistical approach.
Рубрики: Big data.
Artificial intelligence.
Machine learning.
Artificial intelligence.
Big data.
Machine learning.
Аннотация: "This book explores the developing and application of deep learning in big data"--
Доп.точки доступа:
Bouarara, Hadj Ahmed, (1990-) \editor.\
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