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Intelligent Decision Support Systems
by Miquel Sànchez-MarrèThis book presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems
Intelligent Decision Support Systems: Combining Operations Research and Artificial Intelligence - Essays in Honor of Roman Słowiński (Multiple Criteria Decision Making)
by Constantin Zopounidis Jerzy Stefanowski Vincent Mousseau Salvatore GrecoThis book presents a collection of essays written by leading researchers to honor Roman Słowiński’s major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.
Intelligent Decision Support Systems for Smart City Applications (Concise Introductions to AI and Data Science)
by Loveleen Gaur Vernika Agarwal Prasenjit ChatterjeeINTELLIGENT DECISION SUPPORT SYSTEMS FOR SMART CITY APPLICATIONS This book provides smart city frameworks to address new difficulties by adding new features and allowing the city environment to react to collected data and information to increase the efficiency and sustainability of services for inhabitants. Making a smart city is an emerging strategy to mitigate the problems generated by urban population growth and rapid urbanization. This book aims to provide a better understanding of the concept of smart cities and the application of an intelligent decision support system. Based on the analysis of existing information there are eight critical factors of smart city initiatives: management and organization, technology, governance, policy context, people and communities, economy, built infrastructure, and natural environment. This book will focus on the application of the decision support system in managing these eight crucial aspects of smart cities. The intent in writing this book was also to provide a source that covers the stage-by-stage integration of the four key areas involving planning, physical infrastructure, ICT infrastructure, and deploying the smart solutions necessary for city transformation. With this as the motivation, “Decision Support Systems for Smart City Applications” provides the application of an intelligent decision support system for effectively and efficiently managing the transformation process, which can aid various supply chain stakeholders, academic researchers, and related professionals in building smart cities. Various chapters of this book are expected to support practicing managers during the implementation of smart solutions for city transformation. Audience This book is aimed at both academics and practitioners alike in the fields of intelligent computing, decision support systems, the manufacturing industry, supply chain managers, stakeholders, policymakers, and other technical and administrative personnel.
Intelligent Decision Support Systems for Sustainable Computing
by Arun Kumar Sangaiah Ajith Abraham Patrick Siarry Michael ShengThis unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be exploited to create effectual computing systems, and addresses sustainability problems in computing and information processing environments and technologies at the different levels of CI paradigms. An excellent guide to surveying the state of the art in computational intelligence applied to challenging real-world problems in sustainable computing, it is intended for scientists, practitioners, researchers and academicians dealing with the new challenges and advances in area.
Intelligent Decision Support Systems—A Journey to Smarter Healthcare (Intelligent Systems Reference Library #157)
by Smaranda Belciug Florin GorunescuThe goal of this book is to provide, in a friendly and refreshing manner, both theoretical concepts and practical techniques for the important and exciting field of Artificial Intelligence that can be directly applied to real-world healthcare problems. Healthcare – the final frontier. Lately, it seems like Pandora opened the box and evil was released into the world. Fortunately, there was one thing left in the box: hope. In recent decades, hope has been increasingly represented by Intelligent Decision Support Systems. Their continuing mission: to explore strange new diseases, to seek out new treatments and drugs, and to intelligently manage healthcare resources and patients. Hence, this book is designed for all those who wish to learn how to explore, analyze and find new solutions for the most challenging domain of all time: healthcare.
Intelligent Decision Technologies: Proceedings of the 15th KES-IDT 2023 Conference (Smart Innovation, Systems and Technologies #352)
by Ireneusz Czarnowski R. J. Howlett Lakhmi C. JainThis book gathers selected papers from the KES-IDT 2023 Conference, held in Rome, Italy, on June 14–16, 2023. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed is classification, prediction, data analysis, big data, data science, decision support, knowledge engineering and modeling in diverse areas such as finance, cybersecurity, economics, health, management and transportation. The problems in industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues and decision-making theory for economics.
Intelligent Decision Technologies: Proceedings of the 12th KES International Conference on Intelligent Decision Technologies (KES-IDT 2020) (Smart Innovation, Systems and Technologies #193)
by Ireneusz Czarnowski Robert J. Howlett Lakhmi C. JainThis book gathers selected papers from the KES-IDT-2020 Conference, held as a Virtual Conference on June 17–19, 2020. The aim of the annual conference was to present and discuss the latest research results, and to generate new ideas in the field of intelligent decision-making. However, the range of topics discussed during the conference was definitely broader and covered methods in e.g. classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in such diverse areas as finance, cybersecurity, economics, health, management and transportation. The Problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as Intelligent Data Processing and its ApplicationsHigh-Dimensional Data Analysis and its ApplicationsMulti-Criteria Decision Analysis – Theory and ApplicationsLarge-Scale Systems for Intelligent Decision-Making and Knowledge EngineeringDecision Technologies and Related Topics in Big Data Analysis of Social and Financial IssuesDecision-Making Theory for Economics
Intelligent Decision Technologies: Proceedings of the 13th KES-IDT 2021 Conference (Smart Innovation, Systems and Technologies #238)
by Ireneusz Czarnowski Robert J. Howlett Lakhmi C. JainThis book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14–16, 2021. The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discussion about them under the common title "Intelligent Decision Technologies". The conference has been creating for years a platform for knowledge transfer and the generation of new ideas in the field of intelligent decision making.The range of topics discussed during the conference covered methods of classification, prediction, data analysis, big data, decision support, knowledge engineering, modeling, social networks and many more in areas such as finance, economy, management and transportation. The discussed topics covered also decision making for problems regarding the electric vehicle industry.The book contains also several sections devoted to specific topics, such asAdvances in intelligent data processing and its applicationsMulti-criteria decision analysis methodsKnowledge engineering in large-scale systemsHigh-dimensional data analysisSpatial data analysis and sparse estimationInnovative technologies and applications in computer intelligenceIntelligent diagnosis and monitoring of systemsDecision making theory for economics.
Intelligent Decision Technologies: Proceedings of the 14th KES-IDT 2022 Conference (Smart Innovation, Systems and Technologies #309)
by Ireneusz Czarnowski Robert J. Howlett Lakhmi C. JainThis book gathers selected papers from the KES-IDT 2022 Conference, held in Rhodes, Greece on June 20–22, 2022. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed are classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in diverse areas such as finance, cybersecurity, economics, health, management, and transportation. The problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues, and decision-making theory for economics.
Intelligent Decision Technologies
by Rui Neves-Silva Lakhmi C. Jain Robert J. HowlettThis book presents the 57 papers accepted for presentation at the Seventh KES International Conference on Intelligent Decision Technologies (KES-IDT 2015), held in Sorrento, Italy, in June 2015. The conference consists of keynote talks, oral and poster presentations, invited sessions and workshops on the applications and theory of intelligent decision systems and related areas. The conference provides an opportunity for the presentation and discussion of interesting new research results, promoting knowledge transfer and the generation of new ideas. The book will be of interest to all those whose work involves the development and application of intelligent decision systems.
Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II (Smart Innovation, Systems and Technologies #57)
by Ireneusz Czarnowski Alfonso Mateos Caballero Robert J. Howlett Lakhmi C. JainThe KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. The range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. This proceedings contain several sections devoted to specific topics, such as: · Specialized Decision Techniques for Data Mining, Transportation and Project Management · Pattern Recognition for Decision Making Systems · New Advances of Soft Computing in Industrial and Management Engineering · Recent Advances in Fuzzy Systems · Intelligent Data Analysis and Applications · Reasoning-based Intelligent Systems · Intelligent Methods for Eye Movement Data Processing and Analysis · Intelligent Decision Technologies for Water Resources Management · Intelligent Decision Making for Uncertain Unstructured Big Data · Decision Making Theory for Economics · Interdisciplinary Approaches in Business Intelligence Research and Practice · Pattern Recognition in Audio and Speech Processing The KES-IDT conference is a well-established international annual conference, interdisciplinary in nature. These two volumes of proceedings form an excellent account of the latest results and outcomes of recent research in this leading-edge area.
Intelligent Decision Technologies 2016
by Lakhmi C. Jain Robert J. Howlett Alfonso Mateos Caballero Ireneusz CzarnowskiThe KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. The range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. This proceedings contain several sections devoted to specific topics, such as: · Specialized Decision Techniques for Data Mining, Transportation and Project Management · Pattern Recognition for Decision Making Systems · New Advances of Soft Computing in Industrial and Management Engineering · Recent Advances in Fuzzy Systems · Intelligent Data Analysis and Applications · Reasoning-based Intelligent Systems · Intelligent Methods for Eye Movement Data Processing and Analysis · Intelligent Decision Technologies for Water Resources Management · Intelligent Decision Making for Uncertain Unstructured Big Data · Decision Making Theory for Economics · Interdisciplinary Approaches in Business Intelligence Research and Practice · Pattern Recognition in Audio and Speech Processing The KES-IDT conference is a well-established international annual conference, interdisciplinary in nature. These two volumes of proceedings form an excellent account of the latest results and outcomes of recent research in this leading-edge area.
Intelligent Decision Technologies 2018: Proceedings Of The 10th Kes International Conference On Intelligent Decision Technologies (kes-idt 2018) (Smart Innovation, Systems And Technologies #97)
by Ljubo Vlacic Lakhmi C. Jain Robert J. Howlett Ireneusz CzarnowskiThis book gathers the proceedings of the KES-IDT-2018 conference, held in Gold Coast, Queensland, Australia, on June 20–22, 2018 The conference provided opportunities to present and discuss the latest research results, promoting knowledge transfer and the generation of new ideas in the field of intelligent decision-making. The range of topics explored is wide, and includes methods for decision-making, decision support, data analysis, modeling and many more in areas such as finance, economics, management, engineering and transportation. The book contains several sections devoted to specific topics, such as: · Decision-Making Theory for Economics · Advances in Knowledge-based Statistical Data Analysis · On Knowledge-Based Digital Ecosystems & Technologies for Smart and Intelligent Decision Support Systems · Soft Computing Models in Industrial and Management Engineering · Computational Media Computing and its Applications · Intelligent Decision-Making Technologies · Digital Architectures and Decision Management
Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), Volume 2 (Smart Innovation, Systems and Technologies #143)
by Ireneusz Czarnowski Robert J. Howlett Lakhmi C. JainThe book presents a collection of peer-reviewed articles from the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT-19), held Malta on 17–19 June 2019. The conference provided opportunities for the presentation of new research results and discussion about them. It was also an opportunity to generation of new ideas in the field of intelligent decision making. The range of topics explored is wide, and covers methods of classification, prediction, data analysis, decision support, modelling and many more in such areas as finance, cybersecurity, economy, health, management and transportation. The topics cover also problems of data science, signal processing and knowledge engineering.
Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), Volume 1 (Smart Innovation, Systems and Technologies #142)
by Ireneusz Czarnowski Robert J. Howlett Lakhmi C. JainThe book presents a collection of peer-reviewed articles from the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT-19), held Malta on 17–19 June 2019. The conference provided opportunities for the presentation of new research results and discussion about them. It was also an opportunity to generation of new ideas in the field of intelligent decision making. The range of topics explored is wide, and covers methods of classification, prediction, data analysis, decision support, modelling and many more in such areas as finance, cybersecurity, economy, health, management and transportation. The topics cover also problems of data science, signal processing and knowledge engineering.
Intelligent Decision Technology Support in Practice
by Jeffrey W. Tweedale Rui Neves-Silva Lakhmi C. Jain Gloria Phillips-Wren Junzo Watada Robert J. HowlettThis book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications. Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative technique that often represent alternative approaches. This book is suitable for anyone interested in or already working with IDT or Intelligent Decision Support Systems. It is also suitable for students and researchers seeking to learn more about modern Artificial Intelligence and Computational Intelligence techniques that support decision-making in modern computer systems.
Intelligent Diagnosis and Prognosis of Industrial Networked Systems (Automation and Control Engineering #44)
by Chee Khiang Pang Frank L. Lewis Tong Heng Lee Zhao Yang DongIn an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.
Intelligent Distributed Computing IX
by Costin Badica Amal El Fallah Seghrouchni Cesar Analide David Camacho Paulo NovaisThis book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing - IDC'2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL'2015, and of the International Workshop on Future Internet and Smart Networks - FI&SN'2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.
Intelligent Distributed Computing XIII (Studies in Computational Intelligence #868)
by Igor Kotenko Costin Badica Vasily Desnitsky Didier El Baz Mirjana IvanovicThis book gathers research contributions on recent advances in intelligent and distributedcomputing. A major focus is placed on new techniques and applications for several highlydemanded research directions: Internet of Things, Cloud Computing and Big Data, Data Mining and Machine Learning, Multi-agent and Service-Based Distributed Systems, Distributed Algorithms and Optimization, Modeling Operational Processes, Social Network Analysis and Inappropriate Content Counteraction, Cyber-Physical Security and Safety, Intelligent Distributed Decision Support Systems, Intelligent Human-Machine Interfaces, VisualAnalytics and others. The book represents the peer-reviewed proceedings of the 13thInternational Symposium on Intelligent Distributed Computing (IDC 2019), which was held in St. Petersburg, Russia, from October 7 to 9, 2019.
Intelligent Distributed Computing XIV (Studies in Computational Intelligence #1026)
by David Camacho Domenico Rosaci Giuseppe M. L. Sarné Mario VersaciThis book collects 43 regular papers received from 18 countries that present innovative advances in intelligent and distributed computing, encompassing both architectural and algorithmic results related to these fields. Significant attention is given to new models, techniques, and applications for distributed intelligent architectures and high-performance architectures, machine learning techniques, Internet of Things, blockchain, intelligent transport systems, data analytics, trust and reputation systems, and many others. The book includes the peer-reviewed proceedings of the 14th International Symposium on Intelligent Distributed Computing (IDC 2021), which was held in online mode due to the COVSARS2 pandemic situation, during September 16–18, 2021. The IDC 2021 event included sessions on Internet of Things, data analytics, machine learning, multi-agent systems, algorithms, future intelligent transport solutions, blockchain, intelligent distributed computing for cyber-physical security, and security and trust and reputation in intelligent environments.
Intelligent Distributed Computing XV (Studies in Computational Intelligence #1089)
by Lars Braubach Kai Jander Costin BădicăThis book includes the latest research in the diverse field of intelligent distributed computing, covering a multitude of aspects in both distributed computing and intelligent systems. It includes contributions in machine learning, distributed systems & agents, text- and research-centric applications, social systems, and smart cities. It was written by leading experts in the field, who presented their work as part of the 15th International Symposium on Intelligent Distributed Computing (IDC 2022).
Intelligent Distributed Computing XVI: 16th International Symposium on Intelligent Distributed Computing, IDC 2023 (Studies in Computational Intelligence #1138)
by Michael Köhler-Bußmeier Wolfgang Renz Jan SudeikatThis book presents selected contributions to the 16th Symposium on Intelligent Distributed Computing (IDC’23) held from September 13 to 15, 2023, at the HAW Hamburg, Germany. This unique collection of papers presents the latest findings, research achievements and ideas in the area of Intelligent Distributed Computing provided by researchers and practitioners from both distributed computing and intelligent computing communities. Distributed computing covers methods and technology to build complex computational systems composed of collaborating software components scattered across diverse computational elements. Intelligent computing offers a hybrid palette of methods, techniques and their applications ranging from classical artificial intelligence, information and data sciences, multi-agent technologies or computational intelligence to more recent trends such as swarm intelligence, bio-inspired computation, cloud computing, machine learning or social/cyber-physical trust and security.
Intelligent Document Capture with Ephesoft
by Ike Kavas Michael MullerWritten in easy to follow manner, this book is a complete guide to Document capture with Ephesoft,This book is intended for information technology professionals interested in installing and configuring Ephesoft for their organization, but it is a valuable resource for anyone interested in learning about document capture in general.
Intelligent Document Capture with Ephesoft - Second Edition
by Pat Myers Ike KavasAutomate the processing of scanned and digital documents by improving accuracy using web-based open and modern intelligent document capture software About This Book * Learn how to implement the benefits of intelligent document capture using Ephesoft Enterprise 4 * Leverage the power of the open platform to run it as a classic intake capture system to make your current portals or applications more intelligent * A practical guide providing examples for optimizing document capture for your business Who This Book Is For This book is intended for information technology professionals interested in installing and configuring Ephesoft Enterprise for their organization, but it is a valuable resource for anyone interested in learning about intelligent document capture. What You Will Learn * Discover the benefits of using intelligent document capture in your work place * Learn to capture, classify, and separate any type of document * Extract important information from your documents * Transfer the documents and data into your content management system * Customize Ephesoft to meet your unique business requirements * Understand the integration techniques using the Ephesoft web services API * Convert your paper archive to electronic records efficiently * Automate business processes that depend on documents in paper, fax, or email attachment format * Implement distributed capture for mailroom automation In Detail Every organization, public or private, processes documents in various formats, especially paper and fax formats. Processing documents manually is an expensive and time-consuming endeavor. Ephesoft Enterprise is a modern document capture solution that allows an organization to automate the business process. It uses powerful technology to classify and capture the vital information from the document's content. This helps to minimize the time your company spends on reviewing and processing any physical and electronic documents. This book teaches you about document capture in general and implementation of document capture using Ephesoft. Start by learning about document capture and how Ephesoft revolutionized the industry. Progress to a tour of key features, including operator and administrator interfaces and then learn to configure Ephesoft to process your business's specific document types and extract content from those documents. You will also get to know the advanced customization techniques that make Ephesoft accommodate your unique business needs. Finally, the book concludes by teaching you how to embed the classification and extraction functionality using Ephesoft's web services. By the end, you will learn to optimize the processing of your documents, saving your company time and money. Style and approach This is a step-by-step guide on how to configure and use Ephesoft using an accounts payable use case. The book will start with basic techniques and progress to more advanced features that allow you to leverage the power for a modern powerful capture system.
Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries
by Sonali SahuBuild real-world artificial intelligence applications across industries with the help of intelligent document processingKey FeaturesTackle common document processing problems to extract value from any type of documentUnlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/MLApply your knowledge to solve real document analysis problems in various industry applicationsBook DescriptionWith the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs.This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You'll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems.By the end of this AWS book, you'll have mastered the fundamentals of document processing with machine learning through practical implementation.What you will learnUnderstand the requirements and challenges in deriving insights from a documentExplore common stages in the intelligent document processing pipelineDiscover how AWS AI/ML can successfully automate IDP pipelinesFind out how to write clean and elegant Python code by leveraging AIGet to grips with the concepts and functionalities of AWS AI servicesExplore IDP across industries such as insurance, healthcare, finance, and the public sectorDetermine how to apply business rules in IDPBuild, train, and deploy models with serverless architecture for IDPWho this book is forThis book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.