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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence - Softcover
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling.
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence (Paperback or Softback)
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ISBN 10: 196211645X
ISBN 13: 9781962116459
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence (Paperback)
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Paperback. Condition: new. Paperback. Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling. 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 # 9781962116459
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence (Paperback)
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Paperback. Condition: new. Paperback. Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling. 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 # 9781962116459
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence (Paperback)
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Paperback. Condition: new. Paperback. Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling. 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 # 9781962116459
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Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Spatial Correlation and Poverty Prediction Index (PPI) Generation Using Artificial Intelligence examines computational approaches for analyzing spatial relationships and generating poverty prediction indicators through artificial intelligence. The book introduces spatial correlation, socioeconomic data analysis, predictive modeling, machine learning, and geographic data analysis. It considers how spatial patterns and related variables can be examined to identify relationships associated with poverty conditions and support prediction. Attention is given to data preparation, feature representation, spatial analysis, model development, prediction, and evaluation. The discussion connects artificial intelligence with poverty measurement and analytics, providing a foundation for socioeconomic assessment. The book is intended for students, researchers, data scientists, economists, and scientists interested in artificial intelligence, machine learning, spatial analysis, socioeconomic modeling. Seller Inventory # 9781962116459