Pethuru Raj Chelliah – författare
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32 produkter
32 produkter
1 646 kr
Skickas inom 10-15 vardagar
This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics: Cognitive machines and devices Cyber physical systems (CPS) The Internet of Things (IoT) and industrial use cases Industry 4.0 for smarter manufacturing Predictive and prescriptive insights for smarter systems Machine vision and intelligence Natural interfaces K-means clustering algorithm Support vector machine (SVM) algorithm A priori algorithms Linear and logistic regression Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights.This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book’s detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.
696 kr
Skickas inom 10-15 vardagar
This book vividly illustrates all the promising and potential machine learning (ML) and deep learning (DL) algorithms through a host of real-world and real-time business use cases. Machines and devices can be empowered to self-learn and exhibit intelligent behavior. Also, Big Data combined with real-time and runtime data can lead to personalized, prognostic, predictive, and prescriptive insights. This book examines the following topics: Cognitive machines and devices Cyber physical systems (CPS) The Internet of Things (IoT) and industrial use cases Industry 4.0 for smarter manufacturing Predictive and prescriptive insights for smarter systems Machine vision and intelligence Natural interfaces K-means clustering algorithm Support vector machine (SVM) algorithm A priori algorithms Linear and logistic regression Applied Learning Algorithms for Intelligent IoT clearly articulates ML and DL algorithms that can be used to unearth predictive and prescriptive insights out of Big Data. Transforming raw data into information and relevant knowledge is gaining prominence with the availability of data processing and mining, analytics algorithms, platforms, frameworks, and other accelerators discussed in the book. Now, with the emergence of machine learning algorithms, the field of data analytics is bound to reach new heights.This book will serve as a comprehensive guide for AI researchers, faculty members, and IT professionals. Every chapter will discuss one ML algorithm, its origin, challenges, and benefits, as well as a sample industry use case for explaining the algorithm in detail. The book’s detailed and deeper dive into ML and DL algorithms using a practical use case can foster innovative research.
758 kr
Kommande
Data science is a fast-emerging field of study and research. It mainly leverages integrated data analytics platforms, and in the recent past, the arrival of artificial intelligence (AI) technologies and tools to extract actionable insights out of burgeoning data volumes has totally changed the game of data science. Machine and deep learning (ML/DL) algorithms are the principal technologies of the AI paradigm. There are innovations and improvisations in the AI ecosystem that make sense out of a massive quantity of multi-structured data. The data science domain is acquiring special significance these days as businesses and governments across the globe need to fulfil the long-standing goal of data-driven insights and insight-driven decisions. Transitioning data into information and knowledge plays a pivotal role for worldwide enterprises and establishments in effectively initiating and implementing next-generation digital transformation projects.Programming statistics and probability applications are key to this vital transformation of data into knowledge and insight. Probability and statistics are also key to decision-making processes that data science is automating. Demystifying Probability and Statistics for Data Scientists with R illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, this book is written for students and professionals. It is focused on learning outcomes and problem solving. Beginning with the basics of R programming, data science, and probability, the book progresses to methods, testing, and experiment design. Highlights of the book include: Types of data and collection methods Data visualization methods Probability basics Random variables and distributions Sampling methods and confidence intervals and hypothesis testing Design of experiments Correlation and regression Chi square test Non-parametric tests
1 740 kr
Kommande
Data science is a fast-emerging field of study and research. It mainly leverages integrated data analytics platforms, and in the recent past, the arrival of artificial intelligence (AI) technologies and tools to extract actionable insights out of burgeoning data volumes has totally changed the game of data science. Machine and deep learning (ML/DL) algorithms are the principal technologies of the AI paradigm. There are innovations and improvisations in the AI ecosystem that make sense out of a massive quantity of multi-structured data. The data science domain is acquiring special significance these days as businesses and governments across the globe need to fulfil the long-standing goal of data-driven insights and insight-driven decisions. Transitioning data into information and knowledge plays a pivotal role for worldwide enterprises and establishments in effectively initiating and implementing next-generation digital transformation projects.Programming statistics and probability applications are key to this vital transformation of data into knowledge and insight. Probability and statistics are also key to decision-making processes that data science is automating. Demystifying Probability and Statistics for Data Scientists with R illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, this book is written for students and professionals. It is focused on learning outcomes and problem solving. Beginning with the basics of R programming, data science, and probability, the book progresses to methods, testing, and experiment design. Highlights of the book include: Types of data and collection methods Data visualization methods Probability basics Random variables and distributions Sampling methods and confidence intervals and hypothesis testing Design of experiments Correlation and regression Chi square test Non-parametric tests
2 047 kr
Skickas inom 10-15 vardagar
The integration of pioneering information and communication technologies has transformed the hospitality sector. This groundbreaking book delves into the transformative power of cutting-edge technologies in the world of high-end travel and accommodation. As the digital revolution continues to reshape our lives, this book offers an exclusive look at how the hospitality industry is adapting and evolving to cater to the sophisticated tastes of the modern, tech-savvy traveller.In this eye-opening exploration, readers will be taken on a journey through the latest innovations in artificial intelligence, blockchain, and the metaverse as they intersect with the world of luxury hospitality. From AI-driven concierge services and smart hotel rooms that cater to guests' every whim to the democratization of luxury experiences through blockchain-based loyalty programmes and the rise of virtual reality travel, this book reveals the extraordinary possibilities that lie ahead for the discerning traveller.With insights from international experts, this edited collection provides a comprehensive and engaging overview of the current and future trends shaping the industry and will be valuable to scholars and postgraduate researchers across the hospitality sector, innovation, and luxury management.
654 kr
Skickas inom 10-15 vardagar
The integration of pioneering information and communication technologies has transformed the hospitality sector. This groundbreaking book delves into the transformative power of cutting-edge technologies in the world of high-end travel and accommodation. As the digital revolution continues to reshape our lives, this book offers an exclusive look at how the hospitality industry is adapting and evolving to cater to the sophisticated tastes of the modern, tech-savvy traveller.In this eye-opening exploration, readers will be taken on a journey through the latest innovations in artificial intelligence, blockchain, and the metaverse as they intersect with the world of luxury hospitality. From AI-driven concierge services and smart hotel rooms that cater to guests' every whim to the democratization of luxury experiences through blockchain-based loyalty programmes and the rise of virtual reality travel, this book reveals the extraordinary possibilities that lie ahead for the discerning traveller.With insights from international experts, this edited collection provides a comprehensive and engaging overview of the current and future trends shaping the industry and will be valuable to scholars and postgraduate researchers across the hospitality sector, innovation, and luxury management.
Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry
Envisaging AI-inspired Intelligent Energy Systems and Environments
Inbunden, Engelska, 2023
1 424 kr
Skickas inom 5-8 vardagar
The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry Comprehensive resource describing how operations, outputs, and offerings of the oil and gas industry can improve via advancements in AI The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry describes the proven and promising digital technologies and tools available to empower the oil and gas industry to be future-ready. It shows how the widely reported limitations of the oil and gas industry are being nullified through the application of breakthrough digital technologies and how the convergence of digital technologies helps create new possibilities and opportunities to take this industry to its next level. The text demonstrates how scores of proven digital technologies, especially in AI, are useful in elegantly fulfilling complicated requirements such as process optimization, automation and orchestration, real-time data analytics, productivity improvement, employee safety, predictive maintenance, yield prediction, and accurate asset management for the oil and gas industry. The text differentiates and delivers sophisticated use cases for the various stakeholders, providing easy-to-understand information to accurately utilize proven technologies towards achieving real and sustainable industry transformation. The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry includes information on: How various machine and deep learning (ML/DL) algorithms, the prime modules of AI, empower AI systems to deliver on their promises and potentialKey use cases of computer vision (CV) and natural language processing (NLP) as they relate to the oil and gas industrySmart leverage of AI, the Industrial Internet of Things (IIoT), cyber physical systems, and 5G communicationEvent-driven architecture (EDA), microservices architecture (MSA), blockchain for data and device security, and digital twinsClearly expounding how the power of AI and other allied technologies can be meticulously leveraged by the oil and gas industry, The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry is an essential resource for students, scholars, IT professionals, and business leaders in many different intersecting fields.
Model Optimization Methods for Efficient and Edge AI
Federated Learning Architectures, Frameworks and Applications
Inbunden, Engelska, 2024
1 533 kr
Skickas inom 5-8 vardagar
Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problemsGenerating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablersCompressing AI models so that computational, memory, storage, and network requirements can be substantially reducedAddressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous dataOvercoming cyberattacks on mission-critical software systems by leveraging federated learningWritten in an accessible manner and containing a helpful mix of both theoretical concepts and practical applications, Model Optimization Methods for Efficient and Edge AI is an essential reference on the subject for graduate and postgraduate students, researchers, IT professionals, and business leaders.
Generative Artificial Intelligence in Finance
Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes
Inbunden, Engelska, 2025
2 400 kr
Skickas inom 5-8 vardagar
This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management. Audience The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.
1 645 kr
Kommande
Comprehensive resource on graph representation learning (GRL), exploring fundamental principles, advanced methodologies, and case studies A Complete Guide to Graph Representation Learning with Case Studies provides a concise understanding of the subject of graph representation learning (GRL), a rapidly advancing field in the domain of machine learning. The book explores basic concepts to state-of-the-art techniques, enabling readers to progress from a fundamental understanding of the approach to mastering its application. The authors also cover the topics of graph embedding methods, graph neural network (GNN) -based approaches, and the latest trends in GRL such as deep learning, transfer learning, graph pooling, alignment, and matching, and graph machine learning. The book includes examples of applications of graph learning methods with real-world case studies in which the covered methods can be utilized. It also includes innovative solutions to graph machine learning problems such as node classification, link prediction, and unsupervised learning, and discusses neighborhood overlap visualization techniques and overlapping neighborhoods in heterogeneous graphs. Finally, the book provides an overview of open and ongoing research directions and student projects, providing a glimpse into potential avenues for future work. The book also includes information on: Node-level features such as node degree, node centrality, closeness, betweenness, eigenvector, page rank centrality, clustering coefficient, closed triangles, egograph, and motifsNeighborhood sampling techniques such as breadth-first sampling, depth-first sampling, snowball sampling, random walk, shallow walk, edge sampling, link-based sampling, and metapath-based samplingDeep learning models including Graph Autoencoder (GAE), Variational Graph Encoder (VGAE), and Graph Attention Network (GAN)Graph alignment and matching, covering subgraph matching and embedding for matchingA Complete Guide to Graph Representation Learning with Case Studies is a thorough and up-to-date reference on the subject for engineers and researchers in data science and machine learning as well as graduate students in related programs of study.
1 597 kr
Kommande
Exploration of how cutting-edge digital technologies can power humanity’s collective efforts towards urban transport environmental sustainability Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation delves into the nexus between urbanization, transportation, and climate change, providing a comprehensive analysis of how traditional transportation systems contribute to greenhouse gas emissions and air pollution, thereby undermining our collective efforts towards environmental sustainability. Through lucid explanations and real-world examples, the book explores how cutting-edge digital technologies, including Artificial Intelligence (AI), the Internet of Things (IoT), and blockchain, can revolutionize urban transportation. Readers will gain insights into the role of AI-powered platforms and management software solutions that optimize energy usage, enhance efficiency, and promote sustainable mobility. With contributions for a variety of experts in the fields of transportation, environmental science, and artificial intelligence, this book delivers perspectives on topics including: Intelligent traffic management and the impact of computer vision in smart transportationConnected lighting and AI-empowered battery management systemsEdge computing and edge AI for real-time insightsRoute optimization and navigation, smart parking solutions, and fleet and fuel optimizationImplementation of smart microgrids and renewable energy sources such as solar and windWhether you are a policymaker, urban planner, transportation professional, or simply a concerned citizen, Artificial Intelligence (AI) for Smart and Sustainable Urban Transportation serves as a vital resource for understanding the challenges and opportunities in transitioning towards a more sustainable future in the field of urban transportation.
- Nyhet
Next-Generation Recommendation Systems
A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits
Inbunden, Engelska, 2026
1 287 kr
Skickas inom 5-8 vardagar
A detailed guide to building cutting-edge recommendation systems In Next-Generation Recommendation Systems: A Comprehensive Guide to Enabling Technologies and Tools and their Business Benefits, a team of experienced technologists and educators, each with a proven track record in the field, delivers an expert guide to building robust recommendation systems that can interface with complex databases. The authors’ deep understanding of the subject matter is evident as they explain how to use the latest AI technologies, including LLMs, graph neural networks, diffusion models, and generative adversarial networks, to create recommendation engines that users enjoy and that drive business revenue. The book does not just delve into theoretical concepts, but also connects them to advanced implementation techniques. It demonstrates the application of practical and adaptable techniques, such as graph embeddings and Bayesian networks, to solve real-world problems faced by platform users and businesses. Readers will find the knowledge and tools to tackle these challenges head-on. Comprehensive coverage of practical generative AI techniques, including large language models and diffusion modelsDetailed exploration of graph neural networks and knowledge graph embeddings to solve common recommendation engine problemsPractical guidance on implementing generative adversarial networks and variational autoencoders to address mode collapse and information bottleneck challengesIn-depth analysis of hybrid recommendation architectures that combine content-based, collaborative, and knowledge-based filteringReal-world deployment strategies using cloud-native computing environments are not just theoretical concepts in this book. They are actionable strategies that have been tested and proven effective. This emphasis on real-world applicability will reassure readers about the book’s relevance to their professional or academic pursuits. Perfect for data scientists, AI specialists, software engineers, architects, and graduate students, Next-Generation Recommendation Systems is an essential, up-to-date resource for everyone involved in the design, deployment, and optimization of recommendation systems that connect to large, complex datasets.
Building Multi-Agent Large Language Model (LLM) Systems towards Compound AI
Enabling the Transition from Assistant AI to Autonomous AI Systems
Inbunden, Engelska, 2026
1 898 kr
Kommande
Natural Language Processing in Mental Health Care
Methodologies and Clinical Practice
Inbunden, Engelska, 2027
2 165 kr
Kommande
Practical Site Reliability Engineering
Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
Häftad, Engelska, 2018
554 kr
Skickas inom 5-8 vardagar
Create, deploy, and manage applications at scale using SRE principlesKey FeaturesBuild and run highly available, scalable, and secure softwareExplore abstract SRE in a simplified and streamlined wayEnhance the reliability of cloud environments through SRE enhancementsBook DescriptionSite reliability engineering (SRE) is being touted as the most competent paradigm in establishing and ensuring next-generation high-quality software solutions.This book starts by introducing you to the SRE paradigm and covers the need for highly reliable IT platforms and infrastructures. As you make your way through the next set of chapters, you will learn to develop microservices using Spring Boot and make use of RESTful frameworks. You will also learn about GitHub for deployment, containerization, and Docker containers. Practical Site Reliability Engineering teaches you to set up and sustain containerized cloud environments, and also covers architectural and design patterns and reliability implementation techniques such as reactive programming, and languages such as Ballerina and Rust. In the concluding chapters, you will get well-versed with service mesh solutions such as Istio and Linkerd, and understand service resilience test practices, API gateways, and edge/fog computing.By the end of this book, you will have gained experience on working with SRE concepts and be able to deliver highly reliable apps and services.What you will learnUnderstand how to achieve your SRE goalsGrasp Docker-enabled containerization conceptsLeverage enterprise DevOps capabilities and Microservices architecture (MSA)Get to grips with the service mesh concept and frameworks such as Istio and LinkerdDiscover best practices for performance and resiliencyFollow software reliability prediction approaches and enable patternsUnderstand Kubernetes for container and cloud orchestrationExplore the end-to-end software engineering process for the containerized worldWho this book is forPractical Site Reliability Engineering helps software developers, IT professionals, DevOps engineers, performance specialists, and system engineers understand how the emerging domain of SRE comes handy in automating and accelerating the process of designing, developing, debugging, and deploying highly reliable applications and services.
738 kr
Skickas inom 11-20 vardagar
describes the details of cloud migration, the crucial role of monitoring in optimizing the cloud, and the basics of disaster recovery using cloud infrastructure. This technically rigorous yet simple-to-follow textbook is an ideal resource for graduate courses on cloud computing.
Del 1727 - Communications in Computer and Information Science
Internet of Things
Third International Conference, ICIoT 2022, Chennai, India, April 5–7, 2022, Revised Selected Papers
Häftad, Engelska, 2023
714 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed and selected papers presented during the Third International Conference on Internet of Things, ICIoT 2022, held in Chennai, India, in April 2022. The 10 papers were thoroughly reviewed and selected from the 100 qualified submissions.
928 kr
Skickas inom 5-8 vardagar
Numerous advancements are being brought in and incorporated into the cloud domain with the aim of realizing a trove of deeper and decisive automations.Rather than discussing the cloud paradigm in isolation, this fully updated text examines how cloud computing can work collaboratively with other computing models to meet the needs of evolving trends.This multi-dimensional approach encompasses the challenges of fulfilling the storage requirements of big data, the use of the cloud as a remote server for Internet of Things and sensor networks, and an investigation of how cloud computing is interlinked with other established computing phenomenon such as edge computing. New chapters illustrate the distinct ideals of the cloud-native computing, proclaimed as the next-generation cloud computing paradigm.Topics and features:Includes learning objectives, motivating questions, and self-test exercisesIntroduces the underlying concepts, fundamental features, and key technological foundations of cloud computingExamines how enterprise networking and cloud networking can work together to achieve business goalsReviews the different types of cloud storage available to address the evolution of data and the need for digitizationDiscusses the challenges and approaches to implementing cloud governance, security, and the hot topic of cloud managementDescribes the details of cloud migration, the crucial role of monitoring in optimizing the cloud, and the basics of disaster recovery using cloud infrastructureThis technically rigorous, yet simple-to-follow textbook is an ideal resource for graduate courses on cloud computing. Professional software developers and cloud architects will also find the work to be an invaluable reference.
650 kr
Skickas inom 5-8 vardagar
657 kr
Skickas inom 5-8 vardagar
Numerous advancements are being brought in and incorporated into the cloud domain with the aim of realizing a trove of deeper and decisive automations.Rather than discussing the cloud paradigm in isolation, this fully updated text examines how cloud computing can work collaboratively with other computing models to meet the needs of evolving trends.This multi-dimensional approach encompasses the challenges of fulfilling the storage requirements of big data, the use of the cloud as a remote server for Internet of Things and sensor networks, and an investigation of how cloud computing is interlinked with other established computing phenomenon such as edge computing. New chapters illustrate the distinct ideals of the cloud-native computing, proclaimed as the next-generation cloud computing paradigm.Topics and features:Includes learning objectives, motivating questions, and self-test exercisesIntroduces the underlying concepts, fundamental features, and key technological foundations of cloud computingExamines how enterprise networking and cloud networking can work together to achieve business goalsReviews the different types of cloud storage available to address the evolution of data and the need for digitizationDiscusses the challenges and approaches to implementing cloud governance, security, and the hot topic of cloud managementDescribes the details of cloud migration, the crucial role of monitoring in optimizing the cloud, and the basics of disaster recovery using cloud infrastructureThis technically rigorous, yet simple-to-follow textbook is an ideal resource for graduate courses on cloud computing. Professional software developers and cloud architects will also find the work to be an invaluable reference.
1 486 kr
Skickas inom 10-15 vardagar
This book provides extensive information about smart farming, precision agriculture and the technologies that make them succeed. The authors provide detailed machine learning and deep learning models and algorithms that can be implemented effectively to improve smart farming methods. The authors also give elaborate information about the various IoT devices and types of drones that are used vastly in smart farming culture. The authors show specifically how methods and techniques used to improve the crop yield can be executed to help the farmers to improve the agricultural process and cultivation methods using a rule-based methodology. The purpose of this book is to articulate the need for processes, platforms, practices, patterns, and rules to be followed for the better yield of crop production and how IoT, robotics and drones can be used to improve the economy of the countries in the field of agriculture. In a nutshell, the book shows how the combination of multiple cutting-edge technologies leads to the realization of state-of-the-art infrastructures for next-generation agriculture.
1 486 kr
Skickas inom 10-15 vardagar
This book provides extensive information about smart farming, precision agriculture and the technologies that make them succeed. The authors show specifically how methods and techniques used to improve the crop yield can be executed to help the farmers to improve the agricultural process and cultivation methods using a rule-based methodology.
1 857 kr
Skickas inom 10-15 vardagar
This book explains the technologies and tools that underpin GNNs, offering a clear and practical guide to their industrial applications and use cases. AI engineers, data scientists, and researchers in AI and graph theory will find detailed insights into the latest trends and innovations driving this dynamic field. With practical chapters demonstrating how GNNs are reshaping various industry verticals—and how they complement advances in generative, agentic, and physical AI—this book is an essential resource for understanding and leveraging their potential.The neural network paradigm has surged in popularity for its ability to uncover hidden patterns within vast datasets. This transformative technology has spurred global innovations, particularly through the evolution of deep neural networks (DNNs). Convolutional neural networks (CNNs) have revolutionized computer vision, while recurrent neural networks (RNNs) and their advanced variants have automated natural language processing tasks such as speech recognition, translation, and content generation.Traditional DNNs primarily handle Euclidean data, yet many real-world problems involve non-Euclidean data—complex relationships and interactions naturally represented as graphs. This challenge has driven the rise of graph neural networks (GNNs), an approach that extends deep learning into new domains.GNNs are powerful models designed to work with graph-structured data, where nodes represent individual data points and edges denote the relationships between them. Several variants have emerged:Graph Convolutional Networks (GCNs): These networks learn from a node’s local neighborhood by aggregating information from adjacent nodes, updating the node’s representation in the process.Graph Attentional Networks (GATs): By incorporating attention mechanisms, GATs focus on the most relevant neighbors during aggregation, enhancing model performance.Graph Recurrent Networks (GRNs): These networks combine principles from RNNs with graph structures to capture dynamic relationships within the data.GNNs are applied in a variety of advanced use cases, including node classification, link prediction, graph clustering, anomaly detection, recommendation systems, and also in natural language processing and computer vision. They help forecast traffic patterns, analyze molecular structures, verify programs, predict social influence, model electronic health records, and map brain networks.
Reinforcement Learning for the Transportation Industry
A Guide to Implementing RL in Real-world Transportation Scenarios
Inbunden, Engelska, 2026
2 025 kr
Kommande
This book provides a comprehensive exploration of reinforcement learning and its transformative applications in transportation systems. Reinforcement Learning for the Transportation Industry begins with the technical foundations of RL, covering core architectures, formal frameworks, and major algorithms such as Q-learning, Policy Gradient, Actor-Critic, Deep Q-Networks (DQN), and Multi-Agent Reinforcement Learning (MARL). The book further examines Deep Reinforcement Learning (DRL), Reinforcement Learning from Human Feedback (RLHF), Reinforcement Learning from AI Feedback (RLAIF), and Reinforcement Fine-Tuning (RFT), highlighting their growing role in intelligent decision-making and large language models.The later chapters focus on real-world transportation applications, including autonomous vehicles, electric vehicle routing, traffic signal coordination, traffic congestion reduction, ridesharing, transport logistics, advanced air mobility, intelligent transportation systems, and Internet of Vehicles (IoVs). Special attention is given to AutoRL, Federated Reinforcement Learning, and LLM-guided DRL for autonomous driving. By combining theoretical foundations with practical case studies, this book serves as a valuable resource for researchers, academicians, and industry professionals seeking to implement advanced RL solutions for efficient, sustainable, and intelligent transportation systems.
- Nyhet
AI and Cloud Native Software Engineering
Building enterprise-scale cloud-native applications with AI-integrated software engineering workflows (English Edition)
Häftad, Engelska, 2026
432 kr
Skickas inom 5-8 vardagar
Del 1444 - Lecture Notes in Electrical Engineering
Security, Privacy and Data Analytics
Select Proceedings of the 3rd International Conference, ISPDA 2024
Inbunden, Engelska, 2025
2 401 kr
Skickas inom 10-15 vardagar
It covers a wide range of topics, including big data and analytics, cloud security and privacy, data intelligence, hardware security, network security, blockchain technology and distributed ledger, machine learning for security, and more.
Del 1261 - Lecture Notes in Electrical Engineering
Proceedings of the First International Conference on Data Engineering and Machine Intelligence
ICDEMI 2023
Inbunden, Engelska, 2024
3 054 kr
Skickas inom 10-15 vardagar
The proceedings cover recent contributions and novel developments from researchers across industry and academia in data science, data engineering, artificial intelligence, big data, cloud computing, sustainability, and knowledge-based expert systems from technological and social perspectives.
Del 1261 - Lecture Notes in Electrical Engineering
Proceedings of the First International Conference on Data Engineering and Machine Intelligence
ICDEMI 2023
Häftad, Engelska, 2025
3 054 kr
Skickas inom 10-15 vardagar
This volume constitutes peer-reviewed proceedings of the First International Conference on Data Engineering and Machine Intelligence, ICDEMI 2023. The research problems about data engineering and machine learning are covered in this book. The proceedings cover recent contributions and novel developments from researchers across industry and academia in data science, data engineering, artificial intelligence, big data, cloud computing, sustainability, and knowledge-based expert systems from technological and social perspectives. This book will serve as a valuable reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners.
Del 1049 - Lecture Notes in Electrical Engineering
Security, Privacy and Data Analytics
Select Proceedings of the 2nd International Conference, ISPDA 2022
Inbunden, Engelska, 2023
1 966 kr
Skickas inom 10-15 vardagar
The volume covers topics, including big data and analytics, cloud security and privacy, data intelligence, hardware security, network security, blockchain technology and distributed ledger, machine learning for security, and many others.
Del 1049 - Lecture Notes in Electrical Engineering
Security, Privacy and Data Analytics
Select Proceedings of the 2nd International Conference, ISPDA 2022
Häftad, Engelska, 2024
1 966 kr
Skickas inom 10-15 vardagar
The volume covers topics, including big data and analytics, cloud security and privacy, data intelligence, hardware security, network security, blockchain technology and distributed ledger, machine learning for security, and many others.