Machine Intelligence And Big Data In Industry
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Machine Intelligence And Big Data In Industry
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Author : Dominik Ryżko
language : en
Publisher: Springer
Release Date : 2016-03-24
Machine Intelligence And Big Data In Industry written by Dominik Ryżko and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-24 with Technology & Engineering categories.
This book presents valuable contributions devoted to practical applications of Machine Intelligence and Big Data in various branches of the industry. All the contributions are extended versions of presentations delivered at the Industrial Session the 6th International Conference on Pattern Recognition and Machine Intelligence (PREMI 2015) held in Warsaw, Poland at June 30- July 3, 2015, which passed through a rigorous reviewing process. The contributions address real world problems and show innovative solutions used to solve them. This volume will serve as a bridge between researchers and practitioners, as well as between different industry branches, which can benefit from sharing ideas and results.“/p>
Cognitive Computing And Big Data Analytics
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Author : Judith S. Hurwitz
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-12
Cognitive Computing And Big Data Analytics written by Judith S. Hurwitz 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 2015-02-12 with Computers categories.
A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.
Machine Intelligence Big Data Analytics And Iot In Image Processing
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Author : Ashok Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-28
Machine Intelligence Big Data Analytics And Iot In Image Processing written by Ashok Kumar 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 2023-03-28 with Technology & Engineering categories.
MACHINE INTELLIGENCE, BIG DATA ANALYTICS, AND IoT IN IMAGE PROCESSING Discusses both theoretical and practical aspects of how to harness advanced technologies to develop practical applications such as drone-based surveillance, smart transportation, healthcare, farming solutions, and robotics used in automation. The concepts of machine intelligence, big data analytics, and the Internet of Things (IoT) continue to improve our lives through various cutting-edge applications such as disease detection in real-time, crop yield prediction, smart parking, and so forth. The transformative effects of these technologies are life-changing because they play an important role in demystifying smart healthcare, plant pathology, and smart city/village planning, design and development. This book presents a cross-disciplinary perspective on the practical applications of machine intelligence, big data analytics, and IoT by compiling cutting-edge research and insights from researchers, academicians, and practitioners worldwide. It identifies and discusses various advanced technologies, such as artificial intelligence, machine learning, IoT, image processing, network security, cloud computing, and sensors, to provide effective solutions to the lifestyle challenges faced by humankind. Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies. This deliberate choice of covering a diversity of fields was to emphasize the applications of these technologies in almost every contemporary aspect of real life to assist working in different sectors by understanding and exploiting the strategic opportunities offered by these technologies. Audience The book will be of interest to a range of researchers and scientists in artificial intelligence who work on practical applications using machine learning, big data analytics, natural language processing, pattern recognition, and IoT by analyzing images. Software developers, industry specialists, and policymakers in medicine, agriculture, smart cities development, transportation, etc. will find this book exceedingly useful.
Big Data Applications In Industry 4 0
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Author : P. Kaliraj
language : en
Publisher: CRC Press
Release Date : 2022-02-10
Big Data Applications In Industry 4 0 written by P. Kaliraj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Computers categories.
Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making
Machine Learning And Artificial Intelligence With Industrial Applications
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Author : Diego Carou
language : en
Publisher: Springer Nature
Release Date : 2022-03-11
Machine Learning And Artificial Intelligence With Industrial Applications written by Diego Carou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Technology & Engineering categories.
This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
Applications Of Machine Learning In Big Data Analytics And Cloud Computing
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Author : Subhendu Kumar Pani
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Applications Of Machine Learning In Big Data Analytics And Cloud Computing written by Subhendu Kumar Pani 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 Technology & Engineering categories.
Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.
Machine Learning And Big Data
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Author : Uma N. Dulhare
language : en
Publisher: John Wiley & Sons
Release Date : 2020-09-01
Machine Learning And Big Data written by Uma N. Dulhare 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 2020-09-01 with Computers categories.
This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.
Managerial Perspectives On Intelligent Big Data Analytics
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Author : Sun, Zhaohao
language : en
Publisher: IGI Global
Release Date : 2019-02-22
Managerial Perspectives On Intelligent Big Data Analytics written by Sun, Zhaohao and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-22 with Computers categories.
Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.
Artificial Intelligence Big Data And Data Science In Statistics
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Author : Ansgar Steland
language : en
Publisher: Springer Nature
Release Date : 2022-11-15
Artificial Intelligence Big Data And Data Science In Statistics written by Ansgar Steland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Mathematics categories.
This book discusses the interplay between statistics, data science, machine learning and artificial intelligence, with a focus on environmental science, the natural sciences, and technology. It covers the state of the art from both a theoretical and a practical viewpoint and describes how to successfully apply machine learning methods, demonstrating the benefits of statistics for modeling and analyzing high-dimensional and big data. The book’s expert contributions include theoretical studies of machine learning methods, expositions of general methodologies for sound statistical analyses of data as well as novel approaches to modeling and analyzing data for specific problems and areas. In terms of applications, the contributions deal with data as arising in industrial quality control, autonomous driving, transportation and traffic, chip manufacturing, photovoltaics, football, transmission of infectious diseases, Covid-19 and public health. The book will appeal to statisticians and data scientists, as well as engineers and computer scientists working in related fields or applications.
Industrial Machine Learning
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Author : Andreas François Vermeulen
language : en
Publisher: Apress
Release Date : 2019-11-30
Industrial Machine Learning written by Andreas François Vermeulen and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-30 with Computers categories.
Understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI). You will learn to apply ML to data lakes in various industries, supplying data professionals with the advanced skills required to handle the future of data engineering and data science. Data lakes currently generated by worldwide industrialized business activities are projected to reach 35 zettabytes (ZB) as the Fourth Industrial Revolution produces an exponential increase of volume, velocity, variety, variability, veracity, visualization, and value. Industrialization of ML evolves from AI and studying pattern recognition against the increasingly unstructured resource stored in data lakes. Industrial Machine Learning supplies advanced, yet practical examples in different industries, including finance, public safety, health care, transportation, manufactory, supply chain, 3D printing, education, research, and data science. The book covers: supervised learning, unsupervised learning, reinforcement learning, evolutionary computing principles, soft robotics disruptors, and hard robotics disruptors. What You Will Learn Generate and identify transformational disruptors of artificial intelligence (AI) Understand the field of machine learning (ML) and apply it to handle big data and process the data lakes in your environment Hone the skills required to handle the future of data engineering and data science Who This Book Is For Intermediate to expert level professionals in the fields of data science, data engineering, machine learning, and data management