Artificial Intelligence, Optimization, and Data Sciences in Sports
This book delves into the dynamic intersection of data science, data mining, machine learning, and optimization within sports. It compiles and presents the latest achievements in this vibrant and emerging research area, offering a comprehensive overview of how these technologies revolutionize sports...
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| Autor Corporativo: | |
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| Outros Autores: | , , |
| Formato: | Recurso Electrónico livro electrónico |
| Idioma: | inglês |
| Publicado em: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edição: | 1st ed. 2025. |
| Colecção: | Springer Optimization and Its Applications,
218 |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/978-3-031-76047-1 |
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| Resumo: | This book delves into the dynamic intersection of data science, data mining, machine learning, and optimization within sports. It compiles and presents the latest achievements in this vibrant and emerging research area, offering a comprehensive overview of how these technologies revolutionize sports analytics and performance. Topical coverage includes artificial intelligence in sports, automated machine learning for training sessions, computational social science, and deep learning applications. Readers will also explore cutting-edge concepts such as digital twins in sports and sports prediction through data analysis. This volume highlights theoretical advancements and practical case studies that demonstrate real-world applications. Ideal for researchers, practitioners, and students in fields related to sports science, data analytics, and machine learning, this book serves as a crucial resource for anyone looking to understand the transformative impact of technology on sports. Whether you are an academic scholar or a professional working in the industry, this collection offers valuable insights that bridge the gap between research and practical solutions. |
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| Descrição Física: | 1 online resource (XI, 353 p. 60 illus.). 50 illus. in color. |
| ISBN: | 9783031760471 |
| ISSN: | 1931-6836 ; |
| DOI: | 10.1007/978-3-031-76047-1 |