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Big Data Analytics  using Computational Intelligence Approaches
Big Data Analytics  using Computational Intelligence Approaches

Tags: Big Data Analytics, Computational Intelligence Approaches, Big Data Analytics using Computational Intelligence Approaches, Fundamental Concepts of Big Data Analytics, Exploring Big Data Analytics, Data Collection, Pre-Processing in Big Data, Artificial Neural Networks, Syed Ziaur Rahman, Syed Ziaur Rahman atuhor, Syed Ziaur Rahman book, Big Data Analytics notes, Big Data Analytics project, Big Data Analytics course

Big Data Analytics using Computational Intelligence Approaches

This book offers an in-depth analysis of Big Data Analytics, merging the fundamentals of data handling with state-of-the-art computational intelligence methodologies. It presents a comprehensive overview of key principles, including data storage, visualization, and algorithmic strategies, as well as sophisticated uses in Artificial Neural Networks, Fuzzy Logic, Evolutionary Computation, and Swarm Intelligence. Through detailed case studies and practical exercises, this text proves to be an indispensable tool for students, scholars, and experts seeking to apply Big Data technologies in practical problem-solving scenarios.

• Foreword

• Preface

Part I: Foundations and Overview of Big data Analytics

• Introduction

• Fundamental Concepts of Big Data Analytics

• Exploring Big Data Analytics

• Data Collection and Pre-Processing in Big Data

Part II: Computational Intelligence Approaches for Big Data Analytics

• Artificial Neural Networks for Big data Analytics

• Fuzzy Logic for Big Data Analytics

• Evolutionary Computation for Big Data Analytics

• Swarm Intelligence for Big Data Analytics

• Conclusion of the book

• References

• Index


Comprehensive Coverage: Offers a detailed exploration of Big Data Analytics, covering both foundational concepts and advanced computational techniques such as Artificial Neural Networks, Fuzzy Logic, Evolutionary Computation, and Swarm Intelligence.

Real-World Case Studies: Includes numerous practical case studies that demonstrate the application of Big Data technologies across diverse industries, providing readers with hands-on examples of problem-solving.

Step-by-Step Exercises: Provides structured exercises and research problems at the end of each chapter to enhance understanding and encourage active learning and practical application of concepts.

Multi-Disciplinary Approach: Bridges the gap between theory and practice by integrating computational intelligence methods with data science, making the book relevant for students, researchers, and professionals from various disciplines.

Future-Oriented Insights: Discusses future trends in Big Data Analytics, including hybrid algorithms and automated feature selection, offering readers a forward-looking perspective on emerging technologies.

Extensive Reference Material: Contains a comprehensive reference section, making it a valuable resource for academic research and further reading on cutting-edge developments in Big Data and Computational Intelligence.


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