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Beschreibung

Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game--soccer--to illuminate key concepts in predictive modeling and data science. You'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.

Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.

  • Understand machine learning concepts by working with real sports data
  • Develop, refine, and evaluate machine learning models, using Python for data analysis
  • Carry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insights
  • Apply the skills you learn to predictive modeling scenarios in other industries

Struggling to grasp machine learning concepts or unsure how to apply them in the real world? This book aims to change that by using the world's most popular game--soccer--to illuminate key concepts in predictive modeling and data science. You'll develop a solid foundation in machine learning through engaging examples that bridge academic principles with practical applications.

Written by experts in both machine learning and sports analytics, this practical Python-focused guide introduces fundamental data science techniques using real soccer data. Ideal for students, analysts, and soccer fans alike, it offers instructions on models and techniques such as logistic regression, random forests, deep learning, simulations, and feature engineering. But instead of memorizing algorithms, you'll learn by building predictive models to analyze match outcomes, test betting strategies, run simulated game scenarios, and more.

  • Understand machine learning concepts by working with real sports data
  • Develop, refine, and evaluate machine learning models, using Python for data analysis
  • Carry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insights
  • Apply the skills you learn to predictive modeling scenarios in other industries
Über den Autor
Haipeng Gao is a data science and machine learning expert with extensive industry experience building and optimizing large-scale machine learning systems at leading technology companies, including LinkedIn, TikTok, and PayPal. He holds a PhD in Statistics and Operations Research from the University of North Carolina at Chapel Hill, has taught statistics and probability at UNC Chapel Hill and San Jose State University, and holds multiple AI/ML patents granted by the U.S. Patent and Trademark Office.
Details
Erscheinungsjahr: 2026
Genre: Importe, Sport
Produktart: Nachschlagewerke
Rubrik: Hobby & Freizeit
Thema: Ballsport
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9781098181116
ISBN-10: 1098181115
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Gao, Haipeng
Joury, Ari
Shen, Weining
Hu, Guanyu
Hersteller: O'Reilly Media
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 233 x 178 x 18 mm
Von/Mit: Haipeng Gao (u. a.)
Erscheinungsdatum: 31.07.2026
Gewicht: 0,592 kg
Artikel-ID: 135876476

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