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Condizione: New. &Uumlber den AutorDr. Neha Singh is an Assistant Professor in the Electronics & Communication Engineering Department at Manipal University Jaipur, India. Dr. Shilpi Birla is an Associate Professor in the Electronics & C.

Buch. Condizione: Neu. Neuware - Comprehensive resource covering tools and techniques used for predictive analytics with practical applications across various industries.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a detailed exploration of intelligent data modeling concepts integrated with modern machine learning approaches and computational techniques. It focuses on transforming raw and complex datasets into meaningful knowledge using intelligent algorithms, predictive analytics, and automated decision-making systems. The content introduces readers to the foundations of data science, machine learning workflows, data preprocessing, feature engineering, and statistical analysis required for building efficient intelligent models.The book explains various machine learning paradigms including supervised learning, unsupervised learning, reinforcement learning, and deep learning. It discusses important techniques such as classification, regression, clustering, neural networks, ensemble methods, dimensionality reduction, and optimization algorithms. Readers gain an understanding of how intelligent models are designed, trained, evaluated, and deployed in real-world applications.Special emphasis is placed on intelligent data representation, scalable analytics, visualization techniques, and handling large-scale structured and unstructured data. The book also addresses emerging topics including explainable artificial intelligence, ethical machine learning, privacy preservation, and secure data management practices. Practical examples, industry-oriented case studies, and implementation strategies help bridge the gap between theoretical concepts and real-world problem solving.

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a detailed exploration of intelligent data modeling concepts integrated with modern machine learning approaches and computational techniques. It focuses on transforming raw and complex datasets into meaningful knowledge using intelligent algorithms, predictive analytics, and automated decision-making systems. The content introduces readers to the foundations of data science, machine learning workflows, data preprocessing, feature engineering, and statistical analysis required for building efficient intelligent models.The book explains various machine learning paradigms including supervised learning, unsupervised learning, reinforcement learning, and deep learning. It discusses important techniques such as classification, regression, clustering, neural networks, ensemble methods, dimensionality reduction, and optimization algorithms. Readers gain an understanding of how intelligent models are designed, trained, evaluated, and deployed in real-world applications.Special emphasis is placed on intelligent data representation, scalable analytics, visualization techniques, and handling large-scale structured and unstructured data. The book also addresses emerging topics including explainable artificial intelligence, ethical machine learning, privacy preservation, and secure data management practices. Practical examples, industry-oriented case studies, and implementation strategies help bridge the gap between theoretical concepts and real-world problem solving.

Taschenbuch. Condizione: Neu. Intelligent Data Modeling | Machine Learning Approaches and Techniques : Integrating Statistical Learning, Predictive Analytics, and Real-World Applications | Ms. Asha Mary Chacko | Taschenbuch | Englisch | 2026 | Notion Press | EAN 9798904791179 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Buch. Condizione: Neu. Intelligent Data Modeling | Machine Learning Approaches and Techniques : Integrating Statistical Learning, Predictive Analytics, and Real-World Applications | Ms. Asha Mary Chacko | Buch | Englisch | 2026 | Notion Press | EAN 9798904791186 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condizione: Brand New. 272 pages. 6.00x0.63x9.00 inches. In Stock. This item is printed on demand.

Hardcover. Condizione: new. Hardcover. Comprehensive resource covering tools and techniques used for predictive analytics with practical applications across various industries Intelligent Techniques for Predictive Data Analytics provides an in-depth introduction of the tools and techniques used for predictive analytics, covering applications in cyber security, network security, data mining, and machine learning across various industries. Each chapter offers a brief introduction on the subject to make the text accessible regardless of background knowledge. Readers will gain a clear understanding of how to use data processing, classification, and analysis to support strategic decisions, such as optimizing marketing strategies and customer relationship management and recommendation systems, improving general business operations, and predicting occurrence of chronic diseases for better patient management. Traditional data analytics uses dashboards to illustrate trends and outliers, but with large data sets, this process is labor-intensive and time-consuming. This book provides everything readers need to save time by performing deep, efficient analysis without human bias and time constraints. A section on current challenges in the field is also included. Intelligent Techniques for Predictive Data Analytics covers sample topics such as: Models to choose from in predictive modeling, including classification, clustering, forecast, outlier, and time series models Price forecasting, quality optimization, and insect and disease plant and monitoring in agriculture Fraud detection and prevention, credit scoring, financial planning, and customer analytics Big data in smart grids, smart grid analytics, and predictive smart grid quality monitoring, maintenance, and load forecasting Management of uncertainty in predictive data analytics and probable future developments in the field Intelligent Techniques for Predictive Data Analytics is an essential resource on the subject for professionals and researchers working in data science or data management seeking to understand the different models of predictive analytics, along with graduate students studying data science courses and professionals and academics new to the field. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.