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.
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.
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.
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.
Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2016-04-19 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
Download or read book Applications of Computational Intelligence in Data Driven Trading written by Cris Doloc and published by John Wiley & Sons. This book was released on 2019-10-31 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
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
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.
Download or read book Illustrated Computational Intelligence written by Priti Srinivas Sajja and published by Springer Nature. This book was released on 2020-11-16 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a summary of artificial intelligence and machine learning techniques in its first two chapters. The remaining chapters of the book provide everything one must know about the basic artificial intelligence to modern machine intelligence techniques including the hybrid computational intelligence technique, using the concepts of several real-life solved examples, design of projects and research ideas. The solved examples with more than 200 illustrations presented in the book are a great help to instructors, students, non–AI professionals, and researchers. Each example is discussed in detail with encoding, normalization, architecture, detailed design, process flow, and sample input/output. Summary of the fundamental concepts with solved examples is a unique combination and highlight of this book.
Download or read book Enabling AI Applications in Data Science written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-09-23 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.
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.
Download or read book Computational Intelligence and Big Data Analytics written by Ch. Satyanarayana and published by Springer. This book was released on 2018-09-08 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights major issues related to big data analysis using computational intelligence techniques, mostly interdisciplinary in nature. It comprises chapters on computational intelligence technologies, such as neural networks and learning algorithms, evolutionary computation, fuzzy systems and other emerging techniques in data science and big data, ranging from methodologies, theory and algorithms for handling big data, to their applications in bioinformatics and related disciplines. The book describes the latest solutions, scientific results and methods in solving intriguing problems in the fields of big data analytics, intelligent agents and computational intelligence. It reflects the state of the art research in the field and novel applications of new processing techniques in computer science. This book is useful to both doctoral students and researchers from computer science and engineering fields and bioinformatics related domains.
Download or read book Computational Intelligence for Business Analytics written by Witold Pedrycz and published by Springer Nature. This book was released on 2021-10-26 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.
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.
Download or read book Applying Data Science written by Arthur K. Kordon and published by Springer. This book was released on 2021-09-14 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence methods. In Part I, the author introduces a problem-driven approach to implementing AI-based data science and offers practical explanations of key technologies: machine learning, deep learning, decision trees and random forests, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he describes the main steps in creating AI-based data science solutions for business problems, including problem knowledge acquisition, data preparation, data analysis, model development, and model deployment lifecycle. Finally, in Part III the author illustrates the power of AI-based data science with successful applications in manufacturing and business. He also shows how to introduce this technology in a business setting and guides the reader on how to build the appropriate infrastructure and develop the required skillsets. The book is ideal for data scientists who will implement the proposed methodology and techniques in their projects. It is also intended to help business leaders and entrepreneurs who want to create competitive advantage by using AI-based data science, as well as academics and students looking for an industrial view of this discipline.
Download or read book Computational Intelligence in Data Mining written by Giacomo Della Riccia and published by Springer. This book was released on 2014-05-04 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.
Download or read book Lecture Notes in Computational Intelligence and Decision Making written by Sergii Babichev and published by Springer Nature. This book was released on 2021-07-22 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis, and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning creates the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The book contains of 54 science papers which include the results of research concerning the current directions in the fields of data mining, machine learning, and decision making. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Complex Systems and Processes" contains of 26 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 13 papers. There are 15 papers in the third section "Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.
