Operations Research for Social Good
ebook ∣ A Practitioner's Introduction Using SAS and Python
By Natalia Summerville
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Advance your knowledge of operations research and social good!
Recent technological developments allow data analytics practitioners to solve large problems better and faster with state-of-the-art artificial intelligence (AI) tools. At the same time, humanity faces overarching challenges such as the climate crisis, child malnutrition, systemic racism, and global pandemics, among others. Operations Research for Social Good: A Practitioner's Introduction Using SAS and Python showcases operations research (OR) methodologies typically required in engineering curricula to applications targeted to make this world a better place.
Designed for data scientists, analytics and operations research practitioners, and graduate-level students interested in learning optimization modeling with applied use cases, this book provides the skills to model and solve OR problems with both SAS and Python as well as practical tools and tips to bridge the gap between academic learning and real-world implementations based on Data4Good initiatives.
|Advance your knowledge of operations research and social good!
Recent technological developments allow data analytics practitioners to solve large problems better and faster with state-of-the-art artificial intelligence (AI) tools. At the same time, humanity faces overarching challenges such as the climate crisis, child malnutrition, systemic racism, and global pandemics, among others. Operations Research for Social Good: A Practitioner's Introduction Using SAS and Python showcases operations research (OR) methodologies typically required in engineering curricula to applications targeted to make this world a better place.
Designed for data scientists, analytics and operations research practitioners, and graduate-level students interested in learning optimization modeling with applied use cases, this book provides the skills to model and solve OR problems with both SAS and Python as well as practical tools and tips to bridge the gap between academic learning and real-world implementations based on Data4Good initiatives.
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