Business Intelligence Computational Mathematics And Data Analytics

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Business Intelligence Computational Mathematics And Data Analytics

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Author : V. B. Gupta
language : en
Publisher:
Release Date : 2025-06-04

Business Intelligence Computational Mathematics And Data Analytics written by V. B. Gupta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-04 with Business & Economics categories.

This book constitutes the proceedings of the First International Conference on Business Intelligence, Computational Mathematics, and Data Analytics, IBCD 2024, held in Indore, India, during August 18-19, 2024. The conference focus on applied intelligence across data science, mathematics, healthcare, cybersecurity, and business analytics, and will serve as a driving force for transforming theoretical breakthroughs into practical, real-world solutions with meaningful societal impact.

Business Intelligence Computational Mathematics And Data Analytics

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Author : V. B. Gupta
language : en
Publisher: Springer Nature
Release Date : 2025-05-02

Business Intelligence Computational Mathematics And Data Analytics written by V. B. Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.

This book constitutes the proceedings of the First International Conference on Business Intelligence, Computational Mathematics, and Data Analytics, IBCD 2024, held in Indore, India, during August 18–19, 2024. The conference focus on applied intelligence across data science, mathematics, healthcare, cybersecurity, and business analytics, and will serve as a driving force for transforming theoretical breakthroughs into practical, real-world solutions with meaningful societal impact.

Computational Business Analytics

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Author : Subrata Das
language : en
Publisher: CRC Press
Release Date : 2013-12-14

Computational Business Analytics written by Subrata Das and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-14 with Business & Economics categories.

Learn How to Properly Use the Latest Analytics Approaches in Your Organization Computational Business Analytics presents tools and techniques for descriptive, predictive, and prescriptive analytics applicable across multiple domains. Through many examples and challenging case studies from a variety of fields, practitioners easily see the connections to their own problems and can then formulate their own solution strategies. The book first covers core descriptive and inferential statistics for analytics. The author then enhances numerical statistical techniques with symbolic artificial intelligence (AI) and machine learning (ML) techniques for richer predictive and prescriptive analytics. With a special emphasis on methods that handle time and textual data, the text: Enriches principal component and factor analyses with subspace methods, such as latent semantic analyses Combines regression analyses with probabilistic graphical modeling, such as Bayesian networks Extends autoregression and survival analysis techniques with the Kalman filter, hidden Markov models, and dynamic Bayesian networks Embeds decision trees within influence diagrams Augments nearest-neighbor and k-means clustering techniques with support vector machines and neural networks These approaches are not replacements of traditional statistics-based analytics; rather, in most cases, a generalized technique can be reduced to the underlying traditional base technique under very restrictive conditions. The book shows how these enriched techniques offer efficient solutions in areas, including customer segmentation, churn prediction, credit risk assessment, fraud detection, and advertising campaigns.

Machine Learning With R

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Author : Brett Lantz
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-29

Machine Learning With R written by Brett Lantz 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 2023-05-29 with Computers categories.

Learn how to solve real-world data problems using machine learning and R Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features The 10th Anniversary Edition of the bestselling R machine learning book, updated with 50% new content for R 4.0.0 and beyond Harness the power of R to build flexible, effective, and transparent machine learning models Learn quickly with this clear, hands-on guide by machine learning expert Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data. You'll also find this classic R data science book updated to R 4.0.0 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Whether you're looking to take your first steps with R for machine learning or making sure your skills and knowledge are up to date, this is an unmissable read that will help you find powerful new insights in your data. What you will learn Learn the end-to-end process of machine learning from raw data to implementation Classify important outcomes using nearest neighbor and Bayesian methods Predict future events using decision trees, rules, and support vector machines Forecast numeric data and estimate financial values using regression methods Model complex processes with artificial neural networks Prepare, transform, and clean data using the tidyverse Evaluate your models and improve their performance Connect R to SQL databases and emerging big data technologies such as Spark, Hadoop, H2O, and TensorFlow Who this book is for This book is designed to help data scientists, actuaries, data analysts, financial analysts, social scientists, business and machine learning students, and any other practitioners who want a clear, accessible guide to machine learning with R. No R experience is required, although prior exposure to statistics and programming is helpful.

Integration Of Data Mining In Business Intelligence Systems

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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2014-09-30

Integration Of Data Mining In Business Intelligence Systems written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-30 with Computers categories.

Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Edge Computing And Computational Intelligence Paradigms For The Iot

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Author : Nagarajan, G.
language : en
Publisher: IGI Global
Release Date : 2019-06-14

Edge Computing And Computational Intelligence Paradigms For The Iot written by Nagarajan, G. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-14 with Computers categories.

Edge computing is focused on devices and technologies that are attached to the internet of things (IoT). Identifying IoT use across a range of industries and measuring strategic values helps identify what technologies to pursue and can avoid wasted resources on deployments with limited values. Edge Computing and Computational Intelligence Paradigms for the IoT is a critical research book that provides a complete insight on the recent advancements and integration of intelligence in IoT. This book highlights various topics such as disaster prediction, governance, and healthcare. It is an excellent resource for researchers, working professionals, academicians, policymakers, and defense companies.

Applied Mathematics And Computational Intelligence

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Author : Anna M. Gil-Lafuente
language : en
Publisher: Springer
Release Date : 2018-03-06

Applied Mathematics And Computational Intelligence written by Anna M. Gil-Lafuente and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-06 with Technology & Engineering categories.

This book gathers selected papers presented at the conference of the Forum for Interdisciplinary Mathematics (FIM), held at Palau Macaya, Barcelona, on 18 to 20 November, 2015. The event was co-organized by the University of Barcelona (Spain), the Spanish Royal Academy of Economic and Financial Sciences (Spain) and the Forum for Interdisciplinary Mathematics (India). This instalment of the conference was presented with the title “Applied Mathematics and Computational Intelligence” and particularly focused on the use of Mathematics and Computational Intelligence techniques in a diverse range of scientific disciplines, as well as their applications in real-world problems. The book presents thirty peer-reviewed research papers, organised into four topical sections: on Mathematical Foundations; Computational Intelligence and Optimization Techniques; Modelling and Simulation Techniques; and Applications in Business and Engineering. This book will be of great interest to anyone working in the area of applied mathematics and computational intelligence and will be especially useful for scientists and graduate students pursuing research in these fields.

Data Analytics For Business Intelligence

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Author : Zhaohao Sun
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Data Analytics For Business Intelligence written by Zhaohao Sun and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Computers categories.

This book studies data, analytics, and intelligence using Boolean structure. Chapters dive into the theories, foundations, technologies, and methods of data, analytics, and intelligence. The primary aim of this book is to convey the theories and technologies of data, analytics, and intelligence with applications to readers based on systematic generalization and specialization. Sun uses the Boolean structure to deconstruct all books and papers related to data, analytics, and intelligence and to reorganize them to reshape the world of big data, data analytics, analytics intelligence, data science, and artificial intelligence. Multi-industry applications in business, management, and decision-making are provided. Cutting-edge theories, technologies, and applications of data, analytics, and intelligence and their integration are also explored. Overall, this book provides original insights on sharing computing, insight computing, platform computing, a calculus of intelligent analytics and intelligent business analytics, meta computing, data analyticizing, DDPP (descriptive, diagnostic, predictive, and prescriptive) computing, and analytics. This book is a useful resource with multi-industry applications for scientists, engineers, data analysts, educators, and university students.

Computational Intelligence Applications In Business Intelligence And Big Data Analytics

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Author : Vijayan Sugumaran
language : en
Publisher: CRC Press
Release Date : 2017-06-26

Computational Intelligence Applications In Business Intelligence And Big Data Analytics written by Vijayan Sugumaran and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-26 with Computers categories.

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

Data Science And Computational Intelligence

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Author : K. R. Venugopal
language : en
Publisher: Springer
Release Date : 2021-12-07

Data Science And Computational Intelligence written by K. R. Venugopal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-07 with Computers categories.

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.