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Assessing Policy Effectiveness using AI and Language Models

Autor Chandrasekar Vuppalapati
en Limba Engleză Hardback – 31 mai 2024
This volume uses advanced machine learning techniques to analyze government communication to evaluate policy effectiveness. The book develops policy effectiveness foundation models by cohorting historical budget policies with statistical models which are built on well reputed data sources including economic events, macroeconomic trends, and ratings and commerce terms from international institutions. By signal mining policies to the economic outcome patterns, the book aims to create a rich source of successful policy insights in terms of their effectiveness in bringing development to the poor and underserved communities to ensure the spread of wealth, social wellbeing, and standard of living to the common denomination of society rather than a selected quotient. Enabling academics and practitioners across disciplines to develop applications for effective policy interventions, this volume will be of interest to a wide audience including software engineers, data scientists, social scientists, economists, and agriculture practitioners.
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Specificații

ISBN-13: 9783031560965
ISBN-10: 3031560965
Pagini: 492
Ilustrații: XXI, 467 p. 245 illus.
Dimensiuni: 160 x 241 x 32 mm
Greutate: 0.9 kg
Ediția:2024
Editura: Springer
Locul publicării:Cham, Switzerland

Cuprins

Chapter 1: Introduction.- Chapter 2 : Natural Language Models.- Chapter 3: Large Language Models.- Chapter 4 : Macroeconomic Indicators, Aggregates, and Framework.- Chapter 5 : Economic Sustainability.- Chapter 6 : Social Sustainability.- Chapter 7: Conclusion.

Notă biografică

Chandrasekar Vuppalapati is a seasoned Software IT Executive with diverse experience in software technologies, enterprise software architectures, cloud computing, big data business analytics, internet of things (IoT), and software product and program management. He has held engineering and product leadership positions at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies. Chandrasekar has an MS in software engineering from San Jose State University (USA) and an MBA from Santa Clara
University (USA) and currently teaches software engineering, large-scale analytics, data science, mobile computing, cloud technologies, and web and data mining at San Jose State
University (USA).

Textul de pe ultima copertă

This volume uses advanced machine learning techniques to analyze government communication to evaluate policy effectiveness. The book develops policy effectiveness foundation models by cohorting historical budget policies with statistical models which are built on well reputed data sources including economic events, macroeconomic trends, and ratings and commerce terms from international institutions. By signal mining policies to the economic outcome patterns, the book aims to create a rich source of successful policy insights in terms of their effectiveness in bringing development to the poor and underserved communities to ensure the spread of wealth, social wellbeing, and standard of living to the common denomination of society rather than a selected quotient. Enabling academics and practitioners across disciplines to develop applications for effective policy interventions, this volume will be of interest to a wide audience including software engineers, data scientists, social scientists, economists, and agriculture practitioners.

Caracteristici

Develops machine learning linkage models that offer policy recommendations Enables cross-disciplinary cooperation for developing applications to serve marginalized Uses machine learning techniques to analyze government speeches to evaluate policy effectiveness