Mapreduce Based Convolutional Neural Networks

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MapReduce Based Convolutional Neural Networks

Author : Jackie Leung
Publisher :
ISBN 13 :
Total Pages : 47 pages
Book Rating : 4.:/5 (15 download)

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Book Synopsis MapReduce Based Convolutional Neural Networks by : Jackie Leung

Download or read book MapReduce Based Convolutional Neural Networks written by Jackie Leung and published by . This book was released on 2018 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Convolutional neural networks (CNNs) have gained global recognition in advancing the field of artificial intelligence and have had great successes in a wide array of applications including computer vision, speech and natural language processing. However, due to the rise of big data and increased complexity of tasks, the efficiency of training CNNs have been severely impacted. To achieve state-of-art results, CNNs require tens to hundreds of millions of parameters that need to be fine-tuned, resulting in extensive training time and high computational cost. To overcome these obstacles, this thesis takes advantage of distributed frameworks and cloud computing to develop a parallel CNN algorithm. Close examination of the implementation of MapReduce based CNNs as well as how the proposed algorithm accelerates learning are discussed and demonstrated through experiments. Results reveal high accuracy in classification and improvements in speedup, scaleup and sizeup compared to the standard algorithm." -- page ii

Computational Collective Intelligence

Author : Ngoc Thanh Nguyen
Publisher : Springer Nature
ISBN 13 : 3030283747
Total Pages : 702 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Computational Collective Intelligence by : Ngoc Thanh Nguyen

Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer Nature. This book was released on 2019-10-04 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (LNAI 11683 and LNAI 11684) constitutes the refereed proceedings of the 11th International Conference on Computational Collective Intelligence, ICCCI 2019, held in Hendaye France, in September 2019.The 117 full papers presented were carefully reviewed and selected from 200 submissions. The papers are grouped in topical sections on: computational collective intelligence and natural language processing; machine learning in real-world data; distributed collective intelligence for smart manufacturing; collective intelligence for science and technology; intelligent management information systems; intelligent sustainable smart cities; new trends and challenges in education: the university 4.0; intelligent processing of multimedia in web systems; and big data streaming, applications and security.

Deep Learning: Convergence to Big Data Analytics

Author : Murad Khan
Publisher : Springer
ISBN 13 : 9811334595
Total Pages : 79 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Deep Learning: Convergence to Big Data Analytics by : Murad Khan

Download or read book Deep Learning: Convergence to Big Data Analytics written by Murad Khan and published by Springer. This book was released on 2018-12-30 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.

Deep Learning with Hadoop

Author : Dipayan Dev
Publisher : Packt Publishing Ltd
ISBN 13 : 1787121232
Total Pages : 200 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Deep Learning with Hadoop by : Dipayan Dev

Download or read book Deep Learning with Hadoop written by Dipayan Dev and published by Packt Publishing Ltd. This book was released on 2017-02-20 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, implement and scale distributed deep learning models for large-scale datasets About This Book Get to grips with the deep learning concepts and set up Hadoop to put them to use Implement and parallelize deep learning models on Hadoop's YARN framework A comprehensive tutorial to distributed deep learning with Hadoop Who This Book Is For If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book. What You Will Learn Explore Deep Learning and various models associated with it Understand the challenges of implementing distributed deep learning with Hadoop and how to overcome it Implement Convolutional Neural Network (CNN) with deeplearning4j Delve into the implementation of Restricted Boltzmann Machines (RBM) Understand the mathematical explanation for implementing Recurrent Neural Networks (RNN) Get hands on practice of deep learning and their implementation with Hadoop. In Detail This book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop for optimal performance. Starting with understanding what deep learning is, and what the various models associated with deep neural networks are, this book will then show you how to set up the Hadoop environment for deep learning. In this book, you will also learn how to overcome the challenges that you face while implementing distributed deep learning with large-scale unstructured datasets. The book will also show you how you can implement and parallelize the widely used deep learning models such as Deep Belief Networks, Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann Machines and autoencoder using the popular deep learning library deeplearning4j. Get in-depth mathematical explanations and visual representations to help you understand the design and implementations of Recurrent Neural network and Denoising AutoEncoders with deeplearning4j. To give you a more practical perspective, the book will also teach you the implementation of large-scale video processing, image processing and natural language processing on Hadoop. By the end of this book, you will know how to deploy various deep neural networks in distributed systems using Hadoop. Style and approach This book takes a comprehensive, step-by-step approach to implement efficient deep learning models on Hadoop. It starts from the basics and builds the readers' knowledge as they strengthen their understanding of the concepts. Practical examples are included in every step of the way to supplement the theory.

Principles of Big Graph: In-depth Insight

Author :
Publisher : Elsevier
ISBN 13 : 0323898114
Total Pages : 460 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Principles of Big Graph: In-depth Insight by :

Download or read book Principles of Big Graph: In-depth Insight written by and published by Elsevier. This book was released on 2023-01-24 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph. Provides an update on the issues and challenges faced by current researchers Updates on future research agendas Includes advanced topics for intensive research for researchers

Intelligent Systems and Applications

Author : Kohei Arai
Publisher : Springer Nature
ISBN 13 : 3030821935
Total Pages : 897 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Intelligent Systems and Applications by : Kohei Arai

Download or read book Intelligent Systems and Applications written by Kohei Arai and published by Springer Nature. This book was released on 2021-08-03 with total page 897 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents Proceedings of the 2021 Intelligent Systems Conference which is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The conference attracted a total of 496 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process. Of the total submissions, 180 submissions have been selected to be included in these proceedings. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. The chapters include theory and application on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the book interesting and valuable; it provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.

ITNG 2024: 21st International Conference on Information Technology-New Generations

Author : Shahram Latifi
Publisher : Springer Nature
ISBN 13 : 3031565991
Total Pages : 513 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis ITNG 2024: 21st International Conference on Information Technology-New Generations by : Shahram Latifi

Download or read book ITNG 2024: 21st International Conference on Information Technology-New Generations written by Shahram Latifi and published by Springer Nature. This book was released on with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Question Answering over Text and Knowledge Base

Author : Saeedeh Momtazi
Publisher : Springer Nature
ISBN 13 : 3031165527
Total Pages : 208 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Question Answering over Text and Knowledge Base by : Saeedeh Momtazi

Download or read book Question Answering over Text and Knowledge Base written by Saeedeh Momtazi and published by Springer Nature. This book was released on 2022-11-04 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning. After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9. This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge.

Real-Time Applications of Machine Learning in Cyber-Physical Systems

Author : Easwaran, Balamurugan
Publisher : IGI Global
ISBN 13 : 1799893103
Total Pages : 307 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Real-Time Applications of Machine Learning in Cyber-Physical Systems by : Easwaran, Balamurugan

Download or read book Real-Time Applications of Machine Learning in Cyber-Physical Systems written by Easwaran, Balamurugan and published by IGI Global. This book was released on 2022-03-11 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.

Computational Collective Intelligence

Author : Ngoc Thanh Nguyen
Publisher : Springer
ISBN 13 : 9783030283735
Total Pages : 702 pages
Book Rating : 4.2/5 (837 download)

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Book Synopsis Computational Collective Intelligence by : Ngoc Thanh Nguyen

Download or read book Computational Collective Intelligence written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2019-08-10 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (LNAI 11683 and LNAI 11684) constitutes the refereed proceedings of the 11th International Conference on Computational Collective Intelligence, ICCCI 2019, held in Hendaye France, in September 2019.The 117 full papers presented were carefully reviewed and selected from 200 submissions. The papers are grouped in topical sections on: computational collective intelligence and natural language processing; machine learning in real-world data; distributed collective intelligence for smart manufacturing; collective intelligence for science and technology; intelligent management information systems; intelligent sustainable smart cities; new trends and challenges in education: the university 4.0; intelligent processing of multimedia in web systems; and big data streaming, applications and security.

Smart Innovations in Communication and Computational Sciences

Author : Shailesh Tiwari
Publisher : Springer
ISBN 13 : 981132414X
Total Pages : 510 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Smart Innovations in Communication and Computational Sciences by : Shailesh Tiwari

Download or read book Smart Innovations in Communication and Computational Sciences written by Shailesh Tiwari and published by Springer. This book was released on 2018-11-19 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the latest advances and research findings in the fields of computational science and communication. The areas covered include smart innovation; systems and technologies; embedded knowledge and intelligence; innovation and sustainability; advanced computing; and networking and informatics. It also focuses on the knowledge-transfer methodologies and the innovation strategies employed to make these effective. This fascinating compilation appeals to researchers, academics and engineers around the globe.

Advances in Swarm Intelligence

Author : Ying Tan
Publisher : Springer
ISBN 13 : 3319938185
Total Pages : 589 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Advances in Swarm Intelligence by : Ying Tan

Download or read book Advances in Swarm Intelligence written by Ying Tan and published by Springer. This book was released on 2018-06-15 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections namely: multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; predication; classification; finding patterns; image enhancement; deep learning; theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithm; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization.

Computer Networks and Inventive Communication Technologies

Author : S. Smys
Publisher : Springer Nature
ISBN 13 : 981193035X
Total Pages : 909 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Computer Networks and Inventive Communication Technologies by : S. Smys

Download or read book Computer Networks and Inventive Communication Technologies written by S. Smys and published by Springer Nature. This book was released on 2022-10-13 with total page 909 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of peer-reviewed best selected research papers presented at 5th International Conference on Computer Networks and Inventive Communication Technologies (ICCNCT 2022). The book covers new results in theory, methodology, and applications of computer networks and data communications. It includes original papers on computer networks, network protocols and wireless networks, data communication technologies, and network security. The proceedings of this conference is a valuable resource, dealing with both the important core and the specialized issues in the areas of next generation wireless network design, control, and management, as well as in the areas of protection, assurance, and trust in information security practice. It is a reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners for advance work in the area.

Machine Learning and Data Science

Author : Prateek Agrawal
Publisher : John Wiley & Sons
ISBN 13 : 1119775612
Total Pages : 276 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning and Data Science by : Prateek Agrawal

Download or read book Machine Learning and Data Science written by Prateek Agrawal and published by John Wiley & Sons. This book was released on 2022-08-09 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

Machine Learning Hybridization and Optimization for Intelligent Applications

Author : Tanvir Habib Sardar
Publisher : CRC Press
ISBN 13 : 1040130356
Total Pages : 367 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Machine Learning Hybridization and Optimization for Intelligent Applications by : Tanvir Habib Sardar

Download or read book Machine Learning Hybridization and Optimization for Intelligent Applications written by Tanvir Habib Sardar and published by CRC Press. This book was released on 2024-10-28 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using case study-based applications. • Covers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computing. • Explains computing models using real-world examples and dataset-based experiments. • Includes case study-based explanations and usage for machine learning technologies and applications. This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.

Proceedings of the 3rd International Symposium on New Energy and Electrical Technology

Author : Wenping Cao
Publisher : Springer Nature
ISBN 13 : 9819905532
Total Pages : 1010 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Proceedings of the 3rd International Symposium on New Energy and Electrical Technology by : Wenping Cao

Download or read book Proceedings of the 3rd International Symposium on New Energy and Electrical Technology written by Wenping Cao and published by Springer Nature. This book was released on 2023-03-09 with total page 1010 pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference offers a forum for academic and technical communication for researchers and engineers working in the fields of energy science and technology, electrical systems, and power electronics. It conducts in-depth exchanges and discussions on pertinent subjects like new energy and electrical technology. The book aids scholars and engineers worldwide in understanding the academic development trend and expanding their lines of inquiry by disseminating the research status of cutting-edge technologies and scientific research accomplishments. It also strengthens international academic research, academic topics exchange, and discussion, and encourages the industrialization of academic achievements.

e-Infrastructure and e-Services for Developing Countries

Author : Rafik Zitouni
Publisher : Springer Nature
ISBN 13 : 3030415937
Total Pages : 260 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis e-Infrastructure and e-Services for Developing Countries by : Rafik Zitouni

Download or read book e-Infrastructure and e-Services for Developing Countries written by Rafik Zitouni and published by Springer Nature. This book was released on 2020-02-13 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 11th International Conference on e-Infrastructure and e-Services for Developing Countries, AFRICOMM 2019, held in Porto-Novo, Benin, in December 2019. The 19 full papers were carefully selected from 46 submissions. The accepted papers provide a wide range of research topics including targeted infrastructures, Internet of Things (IoT), wireless and mobile networks, intelligent transportation systems (ITS), software and network security, cloud and virtualization, data analytics, and machine learning.