Data Science And Computational Intelligence

Author : Aravindan Chandrabose
Publisher : Springer Nature
ISBN 13 : 3030634671
Total Pages : 338 pages
Book Rating : 4.74/5 ( download)

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Download or read book Computational Intelligence in Data Science written by Aravindan Chandrabose and published by Springer Nature. This book was released on 2020-11-20 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.

Author : Vallidevi Krishnamurthy
Publisher : Springer Nature
ISBN 13 : 3030926001
Total Pages : 229 pages
Book Rating : 4.07/5 ( download)

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Download or read book Computational Intelligence in Data Science written by Vallidevi Krishnamurthy and published by Springer Nature. This book was released on 2021-12-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science.

Author : K. R. Venugopal
Publisher : Springer
ISBN 13 : 9783030912437
Total Pages : 514 pages
Book Rating : 4.34/5 ( download)

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Download or read book Data Science and Computational Intelligence written by K. R. Venugopal and published by Springer. This book was released on 2021-12-07 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised and selected papers from the Sixteenth International Conference on Information Processing, ICInPro 2021, held in Bangaluru, India in October 2021. The 33 full and 9 short papers presented in this volume were carefully reviewed and selected from a total of 177 submissions. The papers are organized in the following thematic blocks: ​Computing & Network Security; Data Science; Intelligence & IoT.

Author : Ayodeji Olalekan Salau
Publisher : CRC Press
ISBN 13 : 1000541754
Total Pages : 272 pages
Book Rating : 4.55/5 ( download)

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Download or read book Computational Intelligence and Data Sciences written by Ayodeji Olalekan Salau and published by CRC Press. This book was released on 2022-03-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents futuristic trends in computational intelligence including algorithms as applicable to different application domains in health informatics covering bio-medical, bioinformatics, and biological sciences. Latest evolutionary approaches to solve optimization problems under biomedical engineering field are discussed. It provides conceptual framework with a focus on application of computational intelligence techniques in the domain of biomedical engineering and health informatics including real-time issues.

Author : Lipo Wang
Publisher : Springer Science & Business Media
ISBN 13 : 3540288031
Total Pages : 280 pages
Book Rating : 4.39/5 ( download)

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Download or read book Data Mining with Computational Intelligence written by Lipo Wang and published by Springer Science & Business Media. This book was released on 2005-12-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions.

Author : Michael R. Berthold
Publisher : Springer Nature
ISBN 13 : 3030455742
Total Pages : 427 pages
Book Rating : 4.43/5 ( download)

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Download or read book Guide to Intelligent Data Science written by Michael R. Berthold and published by Springer Nature. This book was released on 2020-08-06 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results. Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website. This practical and systematic textbook/reference is a “need-to-have” tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a “need to use, need to keep” resource following one's exploration of the subject.

Author : Hamid R. Arabnia
Publisher : Springer Nature
ISBN 13 : 303043981X
Total Pages : 276 pages
Book Rating : 4.11/5 ( download)

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Download or read book Principles of Data Science written by Hamid R. Arabnia and published by Springer Nature. This book was released on 2020-07-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice

Author : Rajendra Akerkar
Publisher : Springer
ISBN 13 : 3319292064
Total Pages : 272 pages
Book Rating : 4.69/5 ( download)

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Download or read book Intelligent Techniques for Data Science written by Rajendra Akerkar and published by Springer. This book was released on 2016-10-11 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions./p> The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Author : Arun Kumar Sangaiah
Publisher : Academic Press
ISBN 13 : 0128133279
Total Pages : 362 pages
Book Rating : 4.79/5 ( download)

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Download or read book Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications written by Arun Kumar Sangaiah and published by Academic Press. This book was released on 2018-08-21 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. Presents a brief overview of computational intelligence paradigms and its significant role in application domains Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing Provides new advances in the fields of CI for bio-engineering application

Author : Tero Tuovinen
Publisher : Springer Nature
ISBN 13 : 3030707873
Total Pages : 278 pages
Book Rating : 4.73/5 ( download)

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Download or read book Computational Sciences and Artificial Intelligence in Industry written by Tero Tuovinen and published by Springer Nature. This book was released on 2021-08-19 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is addressed to young researchers and engineers in the fields of Computational Science and Artificial Intelligence, ranging from innovative computational methods to digital machine learning tools and their coupling used for solving challenging industrial and societal problems.This book provides the latest knowledge from jointly academic and industries experts in Computational Science and Artificial Intelligence fields for exploring possibilities and identifying challenges of applying Computational Sciences and AI methods and tools in industrial and societal sectors.