Overview

Equip yourself with the essentials of informed decision-making with this practical guide to mastering data-driven modeling and extracting actionable, meaningful patterns from the vast sea of modern data. In an era defined by data, the ability to transform raw information into actionable insights is a skill set that transcends industries and disciplines. This book is a comprehensive guide designed to unravel the intricacies of extracting meaningful patterns from the vast sea of data that surrounds us. It explores the significance of data-driven modelling, comparing it to traditional approaches and setting the stage for understanding the transformative power and diverse applications of data-driven techniques. This comprehensive resource empowers readers to leverage data for informed decision-making. Whether you are a novice looking to grasp the fundamentals or an experienced professional seeking advanced techniques, this book serves as a practical guide through the dynamic landscape of data-driven modelling. Through clear explanations, hands-on examples, and real-world applications, readers will gain the skills needed to navigate the complexities of modern data analysis.

Full Product Details

Author:   Arindam Mondal (Dr. B.C. Roy Engineering College, India) ,  Souvik Ganguli (Thapar Institute of Engineering and Technology, Patiala, India)
Publisher:   John Wiley & Sons Inc
Imprint:   Wiley-Scrivener
ISBN:  

9781394287895

ISBN 10:   1394287895
Pages:   320
Publication Date:   07 January 2026
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
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Table of Contents

Preface xv 1 Fundamentals of Data Analysis and Preprocessing 1 Sudipta Hazra and Arindam Mondal 2 Advanced Data Control Methods for Data-Driven Modeling: Techniques, Challenges, and Future Directions 23 Aarushi Chatterjee and Souvik Ganguli 3 Machine Learning Algorithms for Data-Driven Modeling 81 Souryadip Ghosh, Indrani Mukherjee and Suparna Biswas 4 Neural Networks and Deep Learning in Data-Driven Modeling 99 Tanishka Chakraborty, Indrani Mukherjee and Suparna Biswas 5 Advances in Time-Series Analysis: Techniques and Applications for Predictive Forecasting 121 A. UmaDevi, Jagendra Singh, Shrinwantu Raha, Nazeer Shaik, Anil V. Turukmane and Ishaan Singh 6 Ensemble Methods for Data-Driven Modeling in Agriculture and Applications 143 Khalil Ahmed, Mithilesh Kumar Dubey, Kajal and Devendra Kumar Pandey 7 Artificial Intelligence–Enabled Ensemble Machine Learning Approaches for Solanaceae Crops 165 Kajal, Mithilesh Kumar Dubey, Khalil Ahmed and Devendra Kumar Pandey 8 Dynamic Multitask Transfer Learning with Adaptive Feature Sharing for Heterogeneous Data and Continual Learning 187 Toufique Ahammad Gazi 10 Prognosticating Plays: ANN-Enabled Score Projection with the Help of FIS 221 Susmit Chakraborty and Sourish Harh 11 Designing a PID Controller for the Two-Area LFC Problem Using Gradient Descent–Based Linear Regression 239 Susmit Chakraborty and Arindam Mondal 12 Implementing PID Controllers for Data-Driven Recognizing for a Nonlinear System 257 Susmit Chakraborty and Sagnik Agasti 13 Temporal Resilience Redux: BiLSTM for Short-Term Load Forecasting in Deep Learning Domain 273 Ritu K. R. References 292 Index 295

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Author Information

Arindam Mondal, PhD is a Professor at Dr. B.C. Roy Engineering College with more than 20 years of experience. He has published more than 35 papers for scientific and technical journals and conferences. He has 18 patents to his credit and has won several awards for his scholarship. Souvik Ganguli, PhD is an Assistant Professor at the Thapar Institute of Engineering and Technology with more than 19 years of teaching experience. He has published more than 50 papers in leading journals, conferences, and book chapters. He has 15 granted patents to his credit and has won several awards for his scholarly activities.

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