Intelligent Data Modeling: Machine Learning Approaches and Techniques: Integrating Statistical Learning, Predictive Analytics, and Real-World Applications - Softcover
Synopsis
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.
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Paperback. Condition: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798904791179
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Paperback. Condition: new. Paperback. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9798904791179
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Intelligent Data Modeling : Machine Learning Approaches and Techniques : Integrating Statistical Learning, Predictive Analytics, and Real-World Applications
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Taschenbuch. Condition: 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. Seller Inventory # 9798904791179
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Intelligent Data Modeling | Machine Learning Approaches and Techniques : Integrating Statistical Learning, Predictive Analytics, and Real-World Applications
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Taschenbuch. Condition: 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. Seller Inventory # 135417720
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