Ubiquitous Machine Learning And Its Applications

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Ubiquitous Machine Learning And Its Applications

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Author : Kumar, Pradeep
language : en
Publisher: IGI Global
Release Date : 2017-03-03

Ubiquitous Machine Learning And Its Applications written by Kumar, Pradeep and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-03 with Computers categories.

Constant improvements in technological applications have allowed for more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but also ensures that technological progression will continue. Ubiquitous Machine Learning and its Applications is a pivotal reference source for the latest research on the issues and challenges machines face in the new millennium. Featuring extensive coverage on relevant areas such as computational advertising, software engineering, and bioinformatics, this publication is an ideal resource for academicians, graduate students, engineering professionals, and researchers interested in discovering how they can apply these advancements to various disciplines.

Ubiquitous Knowledge Discovery

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Author : Michael May
language : en
Publisher: Springer
Release Date : 2010-10-07

Ubiquitous Knowledge Discovery written by Michael May and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-07 with Computers categories.

Knowledge discovery in ubiquitous environments is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. It aims to provide a unifying framework for systematically investigating the mutual dependencies of otherwise quite unrelated technologies employed in building next-generation intelligent systems: machine learning, data mining, sensor networks, grids, peer-to-peer networks, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others. This state-of-the-art survey is the outcome of a large number of workshops, summer schools, tutorials and dissemination events organized by KDubiq (Knowledge Discovery in Ubiquitous Environments), a networking project funded by the European Commission to bring together researchers and practitioners of this emerging community. It provides in its first part a conceptual foundation for the new field of ubiquitous knowledge discovery - highlighting challenges and problems, and proposing future directions in the area of 'smart', 'adaptive', and 'intelligent' learning. The second part of this volume contains selected approaches to ubiquitous knowledge discovery and treats specific aspects in detail. The contributions have been carefully selected to provide illustrations and in-depth discussions for some of the major findings of Part I.

Deep Learning Applications In Translational Bioinformatics

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Author : Khalid Raza
language : en
Publisher: Elsevier
Release Date : 2024-03-07

Deep Learning Applications In Translational Bioinformatics written by Khalid Raza and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-07 with Technology & Engineering categories.

Deep Learning Applications in Translational Bioinformatics, a new volume in the Advances in Ubiquitous Sensing Application for Healthcare series, offers a detailed overview of basic bioinformatics, deep learning, various applications of deep learning in translational bioinformatics including deep learning ensembles, deep learning in protein classification, detection of various diseases, prediction of antiviral peptides, identification of antibiotic resistance, computer aided drug design and drug formulation. This new volume helps researchers working in the field of machine learning and bioinformatics to foster future research and development in ensemble deep learning and inspire new bioinformatics applications that cannot be attained by using traditional machine learning models. Addresses the practical application of deep learning algorithms to a wide range of bioinformatics challenges Presents integrative and multidisciplinary approaches to ubiquitous healthcare Includes case studies to illustrate the concepts discussed

Advances In Computer Science And Ubiquitous Computing

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Author : James J. Park
language : en
Publisher: Springer Nature
Release Date : 2019-12-03

Advances In Computer Science And Ubiquitous Computing written by James J. Park and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-03 with Technology & Engineering categories.

This book presents the combined proceedings of the 10th International Conference on Computer Science and its Applications (CSA 2018) and the 13th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2018), both held in Kuala Lumpur, Malaysia, Dec 17 - 19, 2018. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing.

Advances In Computer Science And Ubiquitous Computing

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Author : Ji Su Park
language : en
Publisher: Springer Nature
Release Date : 2023-07-04

Advances In Computer Science And Ubiquitous Computing written by Ji Su Park and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Technology & Engineering categories.

This book presents the combined proceedings of the 14th International Conference on Computer Science and its Applications (CSA 2022) and the 16th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2022), both held in Vientiane, Laos, December 19-21, 2022. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies & Computer Science and its Applications. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science and other disciplines related to ubiquitous computing. ​

Current State Of Art In Artificial Intelligence And Ubiquitous Cities

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Author : Rita Yi Man Li
language : en
Publisher: Springer Nature
Release Date : 2022-05-14

Current State Of Art In Artificial Intelligence And Ubiquitous Cities written by Rita Yi Man Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-14 with Technology & Engineering categories.

This book covers artificial intelligence and ubiquitous cities. It discusses the applications of the relevant tools in bringing revolutionary new lives to mankind. It showcases various applications of artificial intelligence in benefiting human society. For example, AI classification shortens the human time required for classifying court cases; humanoid robots help us perform heavy-duty jobs like humans, connect all the smart home devices, and take care of the kids and the elderly. It also presents the application of AutoML to predict housing prices.

Machine Learning For Developers

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Author : Rodolfo Bonnin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-10-26

Machine Learning For Developers written by Rodolfo Bonnin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-26 with Computers categories.

Your one-stop guide to becoming a Machine Learning expert. About This Book Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning A highly practical guide explaining the concepts of problem solving in the easiest possible manner Implement Machine Learning in the most practical way Who This Book Is For This book will appeal to any developer who wants to know what Machine Learning is and is keen to use Machine Learning to make their day-to-day apps fast, high performing, and accurate. Any developer who wants to enter the field of Machine Learning can effectively use this book as an entry point. What You Will Learn Learn the math and mechanics of Machine Learning via a developer-friendly approach Get to grips with widely used Machine Learning algorithms/techniques and how to use them to solve real problems Get a feel for advanced concepts, using popular programming frameworks. Prepare yourself and other developers for working in the new ubiquitous field of Machine Learning Get an overview of the most well known and powerful tools, to solve computing problems using Machine Learning. Get an intuitive and down-to-earth introduction to current Machine Learning areas, and apply these concepts on interesting and cutting-edge problems. In Detail Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the globe is, “How do I get started in Machine Learning?”. One reason could be attributed to the vastness of the subject area because people often get overwhelmed by the abstractness of ML and terms such as regression, supervised learning, probability density function, and so on. This book is a systematic guide teaching you how to implement various Machine Learning techniques and their day-to-day application and development. You will start with the very basics of data and mathematical models in easy-to-follow language that you are familiar with; you will feel at home while implementing the examples. The book will introduce you to various libraries and frameworks used in the world of Machine Learning, and then, without wasting any time, you will get to the point and implement Regression, Clustering, classification, Neural networks, and more with fun examples. As you get to grips with the techniques, you'll learn to implement those concepts to solve real-world scenarios for ML applications such as image analysis, Natural Language processing, and anomaly detections of time series data. By the end of the book, you will have learned various ML techniques to develop more efficient and intelligent applications. Style and approach This book gives you a glimpse of Machine Learning Models and the application of models at scale using clustering, classification, regression and reinforcement learning with fun examples. Hands-on examples will be presented to understand the power of problem solving with Machine Learning and Advanced architectures, software installation, and configuration.

Machine Learning In Java

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Author : AshishSingh Bhatia
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-28

Machine Learning In Java written by AshishSingh Bhatia and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-28 with Mathematics categories.

Leverage the power of Java and its associated machine learning libraries to build powerful predictive models Key FeaturesSolve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET librariesPractical examples, tips, and tricks to help you understand applied machine learning in JavaBook Description As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data. What you will learnDiscover key Java machine learning librariesImplement concepts such as classification, regression, and clusteringDevelop a customer retention strategy by predicting likely churn candidatesBuild a scalable recommendation engine with Apache MahoutApply machine learning to fraud, anomaly, and outlier detectionExperiment with deep learning concepts and algorithmsWrite your own activity recognition model for eHealth applicationsWho this book is for If you want to learn how to use Java's machine learning libraries to gain insight from your data, this book is for you. It will get you up and running quickly and provide you with the skills you need to successfully create, customize, and deploy machine learning applications with ease. You should be familiar with Java programming and some basic data mining concepts to make the most of this book, but no prior experience with machine learning is required.

Intelligent Human Centered Computing

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Author : Siddhartha Bhattacharyya
language : en
Publisher: Springer Nature
Release Date : 2023-06-14

Intelligent Human Centered Computing written by Siddhartha Bhattacharyya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Technology & Engineering categories.

This book features high-quality research papers presented at the First Doctoral Symposium on Human Centered Computing (HUMAN 2023), jointly organized by Computer Society of India, Kolkata Chapter and Techno India University, West Bengal, on February 25, 2023. This book discusses the topics of modern human centered computing and its applications. The book showcases the fusion of human sciences (social and cognitive) with computer science (human–computer interaction, signal processing, machine learning, and ubiquitous computing).

Deep Learning For Medical Decision Support Systems

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Author : Utku Kose
language : en
Publisher: Springer Nature
Release Date : 2020-06-17

Deep Learning For Medical Decision Support Systems written by Utku Kose and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Technology & Engineering categories.

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.