ISBN: 9783725882557 - machine learning and statistical learning with applications 2025 (8 resultados)

Condición: New.

Hardcover. Condición: new. Hardcover. This Special Issue, "Machine Learning and Statistical Learning with Applications 2025", presents a curated collection of recent advances at the intersection of methodological innovation and real-world impact. This Special Issue brings together 14 contributions spanning diverse domains, including healthcare, environmental systems, finance, and socio-technical applications. The articles highlight how modern machine learning approaches, from deep learning and hybrid models to statistical and interpretable methods, are being adapted to address complex, data-intensive problems. A key theme across the collection is the growing emphasis on reliability and applicability. Beyond predictive accuracy, the featured works explore challenges such as interpretability, uncertainty estimation, data scarcity, and deployment in high-stakes environments. Several studies demonstrate the effectiveness of combining traditional statistical techniques with contemporary machine learning models, reflecting a broader trend toward integrated and application-aware solutions. Overall, this Special Issue highlights the evolving role of machine learning and statistical learning as essential tools for data-driven discovery and decision making, while emphasizing the importance of robustness, transparency, and practical relevance in modern research. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. This Special Issue, "Machine Learning and Statistical Learning with Applications 2025", presents a curated collection of recent advances at the intersection of methodological innovation and real-world impact. This Special Issue brings together 14 contributions spanning diverse domains, including healthcare, environmental systems, finance, and socio-technical applications. The articles highlight how modern machine learning approaches, from deep learning and hybrid models to statistical and interpretable methods, are being adapted to address complex, data-intensive problems. A key theme across the collection is the growing emphasis on reliability and applicability. Beyond predictive accuracy, the featured works explore challenges such as interpretability, uncertainty estimation, data scarcity, and deployment in high-stakes environments. Several studies demonstrate the effectiveness of combining traditional statistical techniques with contemporary machine learning models, reflecting a broader trend toward integrated and application-aware solutions. Overall, this Special Issue highlights the evolving role of machine learning and statistical learning as essential tools for data-driven discovery and decision making, while emphasizing the importance of robustness, transparency, and practical relevance in modern research. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condición: new. Hardcover. This Special Issue, "Machine Learning and Statistical Learning with Applications 2025", presents a curated collection of recent advances at the intersection of methodological innovation and real-world impact. This Special Issue brings together 14 contributions spanning diverse domains, including healthcare, environmental systems, finance, and socio-technical applications. The articles highlight how modern machine learning approaches, from deep learning and hybrid models to statistical and interpretable methods, are being adapted to address complex, data-intensive problems. A key theme across the collection is the growing emphasis on reliability and applicability. Beyond predictive accuracy, the featured works explore challenges such as interpretability, uncertainty estimation, data scarcity, and deployment in high-stakes environments. Several studies demonstrate the effectiveness of combining traditional statistical techniques with contemporary machine learning models, reflecting a broader trend toward integrated and application-aware solutions. Overall, this Special Issue highlights the evolving role of machine learning and statistical learning as essential tools for data-driven discovery and decision making, while emphasizing the importance of robustness, transparency, and practical relevance in modern research. 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.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This Special Issue, 'Machine Learning and Statistical Learning with Applications 2025', presents a curated collection of recent advances at the intersection of methodological innovation and real-world impact. This Special Issue brings together 14 contributions spanning diverse domains, including healthcare, environmental systems, finance, and socio-technical applications. The articles highlight how modern machine learning approaches, from deep learning and hybrid models to statistical and interpretable methods, are being adapted to address complex, data-intensive problems. A key theme across the collection is the growing emphasis on reliability and applicability. Beyond predictive accuracy, the featured works explore challenges such as interpretability, uncertainty estimation, data scarcity, and deployment in high-stakes environments. Several studies demonstrate the effectiveness of combining traditional statistical techniques with contemporary machine learning models, reflecting a broader trend toward integrated and application-aware solutions. Overall, this Special Issue highlights the evolving role of machine learning and statistical learning as essential tools for data-driven discovery and decision making, while emphasizing the importance of robustness, transparency, and practical relevance in modern research.…

Buch. Condición: Neu. Machine Learning and Statistical Learning with Applications 2025 | Buch | Englisch | 2026 | MDPI AG | EAN 9783725882557 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.