Book Description
Predictive Intelligence in Public Health and Financial Risk explores the application of predictive analytics, machine learning, and data-driven intelligence to two critical domains: public health and financial risk management. The book examines how large and complex datasets can be analyzed to identify patterns, anticipate risks, and support informed decision-making.
The book presents key concepts in predictive modeling, data analysis, risk assessment, and intelligent decision-support systems. In the public health context, it considers how predictive approaches can support disease surveillance, health risk assessment, population-level analysis, and resource planning. In financial applications, it examines the use of predictive techniques for assessing financial uncertainty, credit risk, market-related risks, and other data-driven financial challenges.
Particular attention is given to the role of machine learning and predictive intelligence in transforming historical and real-time data into actionable insights. The book also highlights important considerations surrounding model performance, data quality, interpretability, uncertainty, and responsible use of predictive systems.
By bringing together perspectives from public health analytics and financial risk management, this book provides a useful reference for students, researchers, data scientists, healthcare analysts, financial professionals, engineers, and practitioners interested in artificial intelligence, machine learning, predictive analytics, and risk intelligence. It is especially relevant to readers seeking to understand how predictive technologies can strengthen planning, forecasting, and evidence-based decision-making across diverse sectors.
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. Book DescriptionPredictive Intelligence in Public Health and Financial Risk explores the application of predictive analytics, machine learning, and data-driven intelligence to two critical domains: public health and financial risk management. The book examines how large and complex datasets can be analyzed to identify patterns, anticipate risks, and support informed decision-making.The book presents key concepts in predictive modeling, data analysis, risk assessment, and intelligent decision-support systems. In the public health context, it considers how predictive approaches can support disease surveillance, health risk assessment, population-level analysis, and resource planning. In financial applications, it examines the use of predictive techniques for assessing financial uncertainty, credit risk, market-related risks, and other data-driven financial challenges.Particular attention is given to the role of machine learning and predictive intelligence in transforming historical and real-time data into actionable insights. The book also highlights important considerations surrounding model performance, data quality, interpretability, uncertainty, and responsible use of predictive systems.By bringing together perspectives from public health analytics and financial risk management, this book provides a useful reference for students, researchers, data scientists, healthcare analysts, financial professionals, engineers, and practitioners interested in artificial intelligence, machine learning, predictive analytics, and risk intelligence. It is especially relevant to readers seeking to understand how predictive technologies can strengthen planning, forecasting, and evidence-based decision-making across diverse sectors. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798240886225
Seller: California Books, Miami, FL, U.S.A.
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Seller: AussieBookSeller, Truganina, VIC, Australia
Paperback. Condition: new. Paperback. Book DescriptionPredictive Intelligence in Public Health and Financial Risk explores the application of predictive analytics, machine learning, and data-driven intelligence to two critical domains: public health and financial risk management. The book examines how large and complex datasets can be analyzed to identify patterns, anticipate risks, and support informed decision-making.The book presents key concepts in predictive modeling, data analysis, risk assessment, and intelligent decision-support systems. In the public health context, it considers how predictive approaches can support disease surveillance, health risk assessment, population-level analysis, and resource planning. In financial applications, it examines the use of predictive techniques for assessing financial uncertainty, credit risk, market-related risks, and other data-driven financial challenges.Particular attention is given to the role of machine learning and predictive intelligence in transforming historical and real-time data into actionable insights. The book also highlights important considerations surrounding model performance, data quality, interpretability, uncertainty, and responsible use of predictive systems.By bringing together perspectives from public health analytics and financial risk management, this book provides a useful reference for students, researchers, data scientists, healthcare analysts, financial professionals, engineers, and practitioners interested in artificial intelligence, machine learning, predictive analytics, and risk intelligence. It is especially relevant to readers seeking to understand how predictive technologies can strengthen planning, forecasting, and evidence-based decision-making across diverse sectors. 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 # 9798240886225
Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. Book DescriptionPredictive Intelligence in Public Health and Financial Risk explores the application of predictive analytics, machine learning, and data-driven intelligence to two critical domains: public health and financial risk management. The book examines how large and complex datasets can be analyzed to identify patterns, anticipate risks, and support informed decision-making.The book presents key concepts in predictive modeling, data analysis, risk assessment, and intelligent decision-support systems. In the public health context, it considers how predictive approaches can support disease surveillance, health risk assessment, population-level analysis, and resource planning. In financial applications, it examines the use of predictive techniques for assessing financial uncertainty, credit risk, market-related risks, and other data-driven financial challenges.Particular attention is given to the role of machine learning and predictive intelligence in transforming historical and real-time data into actionable insights. The book also highlights important considerations surrounding model performance, data quality, interpretability, uncertainty, and responsible use of predictive systems.By bringing together perspectives from public health analytics and financial risk management, this book provides a useful reference for students, researchers, data scientists, healthcare analysts, financial professionals, engineers, and practitioners interested in artificial intelligence, machine learning, predictive analytics, and risk intelligence. It is especially relevant to readers seeking to understand how predictive technologies can strengthen planning, forecasting, and evidence-based decision-making across diverse sectors. 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 # 9798240886225
Quantity: 1 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Book DescriptionPredictive Intelligence in Public Health and Financial Risk explores the application of predictive analytics, machine learning, and data-driven intelligence to two critical domains: public health and financial risk management. The book examines how large and complex datasets can be analyzed to identify patterns, anticipate risks, and support informed decision-making.The book presents key concepts in predictive modeling, data analysis, risk assessment, and intelligent decision-support systems. In the public health context, it considers how predictive approaches can support disease surveillance, health risk assessment, population-level analysis, and resource planning. In financial applications, it examines the use of predictive techniques for assessing financial uncertainty, credit risk, market-related risks, and other data-driven financial challenges.Particular attention is given to the role of machine learning and predictive intelligence in transforming historical and real-time data into actionable insights. The book also highlights important considerations surrounding model performance, data quality, interpretability, uncertainty, and responsible use of predictive systems.By bringing together perspectives from public health analytics and financial risk management, this book provides a useful reference for students, researchers, data scientists, healthcare analysts, financial professionals, engineers, and practitioners interested in artificial intelligence, machine learning, predictive analytics, and risk intelligence. It is especially relevant to readers seeking to understand how predictive technologies can strengthen planning, forecasting, and evidence-based decision-making across diverse sectors. Seller Inventory # 9798240886225
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Predictive Intelligence in Public Health and Financial Risk | Radhika | Taschenbuch | Englisch | 2026 | Pippet Sky | EAN 9798240886225 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 136405022