Automated Machine Learning And Industrial Applications
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Automated Machine Learning And Industrial Applications
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Author : E. Gangadevi
language : en
Publisher: John Wiley & Sons
Release Date : 2025-07-23
Automated Machine Learning And Industrial Applications written by E. Gangadevi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-23 with Computers categories.
The book provides a comprehensive understanding of Automated Machine Learning’s transformative potential across various industries, empowering users to seamlessly implement advanced machine learning solutions without needing extensive expertise. Automated Machine Learning (AutoML) is a process to automate the responsibilities of machine learning concepts for real-world problems. The AutoML process is comprised of all steps, beginning with a raw dataset and concluding with the construction of a machine learning model for deployment. The purpose of AutoML is to allow non-experts to work with machine learning models and techniques without requiring much knowledge in machine learning. This advancement enables data scientists to produce the easiest solutions and most accurate results within a short timeframe, allowing them to outperform normal machine learning models. Meta-learning, neural network architecture, and hyperparameter optimization, are applied based on AutoML. Automated Machine Learning and Industrial Applications offers an overview of the basic architecture, evolution, and applications of AutoML. Potential applications in healthcare, banking, agriculture, aerospace, and security are discussed in terms of their frameworks, implementation, and evaluation. This book also explores the AutoML ecosystem, its integration with blockchain, and various open-source tools available on the AutoML platform. It serves as a practical guide for engineers and data scientists, offering valuable insights for decision-makers looking to integrate machine learning into their workflows. Readers will find the book: Aims to explore current trends such as augmented reality, virtual reality, blockchain, open-source platforms, and Industry 4.0; Serves as an effective guide for professionals, researchers, industrialists, data scientists, and application developers; Explores technologies such as IoT, blockchain, artificial intelligence, and robotics, serving as a core guide for undergraduate and postgraduate students. Audience Data and computer scientists, research scholars, professionals, and industrialists interested in technology for Industry 4.0 applications.
Automated Machine Learning And Industrial Applications
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Author : E. Gangadevi
language : en
Publisher: John Wiley & Sons
Release Date : 2025-09-02
Automated Machine Learning And Industrial Applications written by E. Gangadevi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-02 with Computers categories.
The book provides a comprehensive understanding of Automated Machine Learning’s transformative potential across various industries, empowering users to seamlessly implement advanced machine learning solutions without needing extensive expertise. Automated Machine Learning (AutoML) is a process to automate the responsibilities of machine learning concepts for real-world problems. The AutoML process is comprised of all steps, beginning with a raw dataset and concluding with the construction of a machine learning model for deployment. The purpose of AutoML is to allow non-experts to work with machine learning models and techniques without requiring much knowledge in machine learning. This advancement enables data scientists to produce the easiest solutions and most accurate results within a short timeframe, allowing them to outperform normal machine learning models. Meta-learning, neural network architecture, and hyperparameter optimization, are applied based on AutoML. Automated Machine Learning and Industrial Applications offers an overview of the basic architecture, evolution, and applications of AutoML. Potential applications in healthcare, banking, agriculture, aerospace, and security are discussed in terms of their frameworks, implementation, and evaluation. This book also explores the AutoML ecosystem, its integration with blockchain, and various open-source tools available on the AutoML platform. It serves as a practical guide for engineers and data scientists, offering valuable insights for decision-makers looking to integrate machine learning into their workflows. Readers will find the book: Aims to explore current trends such as augmented reality, virtual reality, blockchain, open-source platforms, and Industry 4.0; Serves as an effective guide for professionals, researchers, industrialists, data scientists, and application developers; Explores technologies such as IoT, blockchain, artificial intelligence, and robotics, serving as a core guide for undergraduate and postgraduate students. Audience Data and computer scientists, research scholars, professionals, and industrialists interested in technology for Industry 4.0 applications.
Deep Learning Techniques For Automation And Industrial Applications
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Author : Pramod Singh Rathore
language : en
Publisher: John Wiley & Sons
Release Date : 2024-07-23
Deep Learning Techniques For Automation And Industrial Applications written by Pramod Singh Rathore and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-23 with Computers categories.
This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. “Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful.
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0
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Author : Jayesh Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-14
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0 written by Jayesh Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.
Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary to provide perspective on the implications as one continuous stream of technology. It then discusses scalable and adaptive deep learning algorithms, which work in modern machine learning systems where there is a deluge of data. These algorithms sufficiently prepare AI technologies to face the challenges of increasing data as well as expansion of computational capabilities. Chapter three is Federated learning for Edge AI further makes privacy / personalization and security stronger. The amalgamation of blockchain emphasizes the robust and distributed nature of edge intelligence in modern IoT ecosystems. One of the most pressing issues in today's ethical landscape is that of Explainable Artificial Intelligence (XAI), and so the fourth chapter deals with some recent advances in explaining black-box models, providing a way to better understand -and thus potentially trust- AI-driven decision-making processes. This study explores the application of Automated Machine Learning (AutoML) in the contexts of Industry 4.0 and Society 5.0 giving insights on how automation can bring efficiency and innovation in different sectors. It also presents information on the challenges and opportunities that AutoML faces. In conclusion, the book discusses Artificial General Intelligence (AGI), which is a new topic that presents an ambitious view of what AI may be capable of in the future and some points to digest over how the concept might relate to our understanding on what industry may look like in the next stage of human evolution. Individually, these chapters offer a slice of the overall picture of where AI technologies are headed to keep pace with an advancing world.
Cyber Physical Systems And Supporting Technologies For Industrial Automation
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Author : R., Thanigaivelan
language : en
Publisher: IGI Global
Release Date : 2023-08-07
Cyber Physical Systems And Supporting Technologies For Industrial Automation written by R., Thanigaivelan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-07 with Technology & Engineering categories.
The exchange of data is the most significant feature of cyber-physical systems (CPS). There are definite advantages and limitations of CPS that must be considered in order to be utilized appropriately across various fields and disciplines. Cyber-Physical Systems and Supporting Technologies for Industrial Automation discusses the latest trends of cyber-physical systems in healthcare, manufacturing processes, energy, and the mobility industry. The book also focuses on advanced subsystems required for the communication of real-time data. Covering key topics such as supporting technologies, Industry 4.0, and manufacturing, this premier reference source is ideal for computer scientists, engineers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Mastering Automated Machine Learning Concepts Tools And Techniques
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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-17
Mastering Automated Machine Learning Concepts Tools And Techniques written by Peter Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with Computers categories.
"Mastering Automated Machine Learning: Concepts, Tools, and Techniques" is an essential guide for anyone seeking to unlock the full potential of Automated Machine Learning (AutoML), a groundbreaking technology transforming the field of data science. By automating complex and time-consuming processes, AutoML is making machine learning more efficient and accessible to a broader range of professionals. This book offers an in-depth exploration of core principles, state-of-the-art methodologies, and the practical tools that define AutoML. From data preparation and feature engineering to model selection, tuning, and deployment, readers will acquire a thorough understanding of how AutoML streamlines the entire machine learning pipeline. Whether you're a data scientist, machine learning engineer, or software developer eager to harness the power of automation, "Mastering Automated Machine Learning" provides the insights you need to implement cutting-edge AutoML solutions. With practical examples and guidance on using Python-based frameworks, this book equips you to revolutionize your data science projects. Embrace the future of machine learning and optimize your workflows with "Mastering Automated Machine Learning: Concepts, Tools, and Techniques."
Machine Learning Techniques And Industry Applications
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Author : Srivastava, Pramod Kumar
language : en
Publisher: IGI Global
Release Date : 2024-04-16
Machine Learning Techniques And Industry Applications written by Srivastava, Pramod Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-16 with Computers categories.
In today's rapidly evolving world, the exponential growth of data poses a significant challenge. As data volumes increase, traditional methods of analysis and decision-making become inadequate. This surge in data complexity calls for innovative solutions that efficiently extract meaningful insights. Machine learning has emerged as a powerful tool to address this challenge, offering algorithms and techniques to analyze large datasets and uncover hidden patterns, trends, and correlations. Machine Learning Techniques and Industry Applications demystifies machine learning through detailed explanations, examples, and case studies, making it accessible to a broad audience. Whether you're a student, researcher, or practitioner, this book equips you with the knowledge and skills needed to harness the power of machine learning to address diverse challenges. From e-government to healthcare, cyber-physical systems to agriculture, this book explores how machine learning can drive innovation and sustainable development.
Examining The Impact Of Deep Learning And Iot On Multi Industry Applications
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Author : Raut, Roshani
language : en
Publisher: IGI Global
Release Date : 2021-01-29
Examining The Impact Of Deep Learning And Iot On Multi Industry Applications written by Raut, Roshani and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-29 with Computers categories.
Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Generative Artificial Intelligence Ai Approaches For Industrial Applications
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Author : Narasimha Rao Vajjhala
language : en
Publisher: Springer Nature
Release Date : 2025-02-03
Generative Artificial Intelligence Ai Approaches For Industrial Applications written by Narasimha Rao Vajjhala and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-03 with Computers categories.
"Generative Artificial Intelligence (AI) Approaches for Industrial Applications" explores the transformative potential of Generative AI technologies across various industries. With contributions from international scholars and experts, this book provides a comprehensive overview of the latest trends, mathematical foundations, and practical applications of Generative AI models. Key sections examine the fundamental concepts of Generative AI, including Generative Adversarial Networks (GANs) and their ethical and security considerations. Special attention is given to the revolutionary impact of Generative AI in healthcare technologies, clinical decision-making, and predictive maintenance within the manufacturing sector. Additionally, the role of Generative AI in FinTech, particularly in redefining business models and enhancing digital security, is thoroughly examined. This book features cutting-edge research on text summarization, age progression using GANs, and integrating AI with regulatory practices. This book is a vital resource for academics, professionals, and practitioners bridging the gap between theoretical AI frameworks and their real-world industrial applications, offering insights into how Generative AI is shaping the future of industries worldwide.
Artificial Intelligence For Digitising Industry Applications
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Author : Ovidiu Vermesan
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Artificial Intelligence For Digitising Industry Applications written by Ovidiu Vermesan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Medical categories.
This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.