How major league baseball teams are using data science and deep learning for to better predict outcomes and game strategy
Sports analytics today is more than a matter of analyzing box scores and play-by-play statistics. Faced with detailed on-field or on-court data from every game, sports teams face challenges in data management, data engineering, and analytics. Thomas Miller details the challenges faced by a Major Lea...
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| Format: | Online |
| Sprache: | eng |
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O'Reilly Media, Inc.
2019
Sebastopol, CA O'Reilly Media Inc. |
| Ausgabe: | 1st edition |
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| Online Zugang: | https://learning.oreilly.com/library/view/-/0636920421467/?ar |
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Tag hinzufügen | Zusammenfassung: | Sports analytics today is more than a matter of analyzing box scores and play-by-play statistics. Faced with detailed on-field or on-court data from every game, sports teams face challenges in data management, data engineering, and analytics. Thomas Miller details the challenges faced by a Major League Baseball team as it sought competitive advantage through data science and deep learning. |
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| Beschreibung: | 1 Online-Ressource (1 video file, approximately 32 min.) |