Neuware - The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. The book illustrates important topics such as data testing a parametric hypothesis, data testing a non-parametric hypothesis, exploratory data analysis, outlier detection and interpretation.This book: - Covers various data analysis tools such as KNIME, RapidMiner, Rstudio, Grafana, and Redash - Discusses the theoretical concept of inference and machine learning algorithms for designing dynamic dashboards - Presents statistical modelling techniques with an emphasis on pattern mining, and pattern relationships - Explains the problem of efficient retrieval of similar time series in large databases to enrich the knowledge of the readers to effectively handle various real-time datasets - Illustrates dimensionality reduction techniques such as principal component analysis, linear discriminant analysis, singular value decomposition, and piecewise vector quantized approximation It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

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Detalles bibliogr�ficos

T�tulo: Interactive and Dynamic Dashboard : Design Principles
Editor: Taylor & Francis Ltd Jul 2026
Fecha de publicaci�n: 2026
Idioma: Ingl�s
ISBN 10: 1032894210
ISBN 13: 9781032894218
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 234�mil�metros de ancho por 156 de alto por 16 de largo
Peso: 427 gramos

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Sinopsis

The text comprehensively discusses the representation of visual data and design principles of interactive and dynamic dashboards. It further covers the theoretical concept of inference and machine learning algorithms for making the concepts clear to the reader. The book illustrates important topics such as data testing a parametric hypothesis, data testing a non-parametric hypothesis, exploratory data analysis, outlier detection and interpretation.

This book:

Covers various data analysis tools such as KNIME, RapidMiner, Rstudio, Grafana, and Redash

Discusses the theoretical concept of inference and machine learning algorithms for designing dynamic dashboards

Presents statistical modelling techniques with an emphasis on pattern mining, and pattern relationships

Explains the problem of efficient retrieval of similar time series in large databases to enrich the knowledge of the readers to effectively handle various real-time datasets

Illustrates dimensionality reduction techniques such as principal component analysis, linear discriminant analysis, singular value decomposition, and piecewise vector quantized approximation

It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.

Acerca del autor

A. Vadivel received his master’s degree in science from NITT. He pursued Masters in Technology and Doctorate of Philosophy from Indian Institute of Technology (IIT), Kharagpur, India. He had 13 years of Technical Experience in Network Engineering & Instrumentation Engineering in IIT-Kharagpur, and sixteen years of teaching experience. Currently he is working as Professor in Department of Artificial Intelligence and Data Science, GITAM School of Technology, GITAM University, Bengaluru, India. He has published papers in more than 120 international journals and conferences. His Research areas are Content-Based Image and Video Retrieval, Multimedia Information Retrieval from Distributed Environment, Medical Image Analysis, Object Tracking in Motion Video and Cognitive Science. He has received Young Scientist Award by Department of Science and Technology, Govt. of India in 2007, Indo-US Research Fellow Award by Indo-US Science and Technology Forum in 2008. Obama-Singh Knowledge Initiative Award in 2013. Under his guidance, five PhD were awarded, and five PhD scholars are pursuing their degree. He is recognized as research supervisor for GITAM University, National Institute of Technology (NIT), Trichy. He has four Indian patents to his credit.

K Meena received her PhD from Manonmaniam Sundaranar University in 2014. She completed her M.E degree in CSE and B.E degree in ECE from Manonmaniam Sundaranar University in the year 2009 and 2002 respectively. She had 20 years of teaching experience in various reputed organizations. Currently, she is working as Professor in the Department of Computer Science and Engineering, GITAM School of Technology, GITAM University, Bengaluru, India. She has published papers in more than 110 international journals and conferences. Her research areas are Biometrics, Machine learning for information retrieval, Computer vision, and Medical Data Analysis. Under her guidance, four PhD were awarded, and five PhD scholars are pursuing their degree. She is recognized as research supervisor for GITAM University, Vel Tech University and Anna University. She has 6 Indian Patents and 1 Australian Patents to her credit.

P. Sumathy received her master’s degree and bachelor’s degree from Bharathidasan University, Trichy She received her PhD from Gandhigram Rural Institute (Deemed to be University), Dindugal. She had 18 years of teaching experience in various reputed organizations. Currently she is working as Assistant Professor of Computer Science Engineering and Applications, Bharathidasan University. She has published papers in more than 70 international journals and conferences. Her Research areas are Content-Based Image and Video Retrieval, Multimedia Information Retrieval from Distributed Environment, Object Tracking in Motion Video and Cognitive Science. Under her guidance, two PhD were awarded, and five PhD scholars are pursuing their degree. She is recognized as research supervisor for Bharathidasan University.

Henry Selvaraj working as Professor in the Department of Electrical and Computer Engineering, University of Nevada, Las Vegas, USA. His research interests include Logic Synthesis, Digital Design, Programmable Devices, Artificial Intelligence, Multiple Valued Functions, Digital Signal Processing, Bio-medical Image Processing, Networks, Path Planning and Object Tracker in Video Sequence. He has 36 years of teaching and research experience. He guided five research scholars in various domains such as Artificial Intelligence, Digital design and video analytics.

P. Shanmugavadivu is currently the Professor and Head, Department of Computer Science and Applications, at The Gandhigram Rural Institute (Deemed to be University), and is involved in Teaching, Research, and Extension. She has 31 years of Academic experience and 22 years of research experience. Her research areas include Medical Image Analysis, Healthcare Analytics, Parallel Computing, Software Engineering and Content-Based Image Retrieval. Under her guidance, TEN PhDs were awarded; presently EIGHT Ph.D. scholars are pursuing their degree. She has published 51 research articles in International Journals and 87 International/National Conferences and 19 book chapters. She has authored two research books and three edited volumes. She serves as an Editorial Board Member of two Journals. She is sanctioned with funded major research projects of UGC, DST, ICMR and PMMMNMTT for an outlay of Rs.2.39 Cr. She serves as the coordinator for her department’s funding schemes, under UGC-SAP DRS-I (Rs.40 Lakhs) and DST-FIST (Rs.45 Lakhs).

Shaila S.G. is a Professor and Chairperson for the Data Science Program in the Department of Computer Science & Engineering. She earned her PhD in Computer Science from National Institute of Technology, Tiruchirapalli, Tamil Nadu for her thesis on “Multimedia Information Retrieval in Distributed System”. She has 17 years of experience in teaching & research in the concerned field. She has worked for Central Power Research Institute as a Trainee Engineer. Later, she worked as a Junior Research Fellow for a project funded by Dept. of Science and Technology (DST), India for a period of 3 years. She has also worked in Indo-US collaborated project in a Student Exchange program for “Obama-Singh Knowledge Initiative Program” in the University of Nevada (UNLV), Las Vegas, United States. She is a certified IBM trainer for the Business Intelligence. Her research areas are Data mining, Information Retrieval, Image Processing and Computational Neuroscience. She has published more than 45 research articles in reputed Journals and Conferences, books and book chapters. She has 11 Indian Patents and 2 Australian Patents.

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