Isbn: 9781098181116 - soccer analytics with machine learning: learning predictive modeling techniques with sports data (30 resultados)

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  • Idioma: Inglés

    Editorial: O'Reilly Media 7/21/2026, 2026

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    Paperback or Softback. Condición: New. Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data. Book.

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    Paperback. Condición: New. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries.…

  • Idioma: Inglés

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

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  • Idioma: Inglés

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  • Idioma: Inglés

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    paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Idioma: Inglés

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  • Idioma: Inglés

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    Paperback. Condición: New. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries.…

  • Idioma: Inglés

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  • Idioma: Inglés

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    Paperback. Condición: Brand New. 300 pages. 9.19x7.00x9.19 inches. In Stock.

  • Idioma: Inglés

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  • Idioma: Inglés

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  • Idioma: Inglés

    Editorial: O'reilly Media Sep 2026, 2026

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condición: Neu. Neuware -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 300 pp. Englisch.…

  • Idioma: Inglés

    Editorial: O'reilly Media Sep 2026, 2026

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    Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK

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    Taschenbuch. Condición: Neu. Neuware -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 300 pp. Englisch.…

  • Idioma: Inglés

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    Librería: Wegmann1855, Zwiesel, AlemaniaWegmann1855

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    Taschenbuch. Condición: Neu. Neuware -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.…

  • Idioma: Inglés

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  • Idioma: Inglés

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  • Idioma: Inglés

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    Paperback. Condición: New. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries.…

  • Idioma: Inglés

    Editorial: O'reilly Media Sep 2026, 2026

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    Taschenbuch. Condición: Neu. Neuware - 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.…

  • Idioma: Inglés

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  • Idioma: Inglés

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  • Idioma: Inglés

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    Paperback. Condición: new. Paperback. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

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    Taschenbuch. Condición: Neu. Soccer Analytics with Machine Learning | Learning Predictive Modeling Techniques with Sports Data | Haipeng Gao (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2026 | O'Reilly Media | EAN 9781098181116 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

  • Idioma: Inglés

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    Taschenbuch. Condición: Neu. Neuware -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 industriesLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 300 pp. Englisch.…

  • Idioma: Inglés

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    Paperback. Condición: New. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply the skills you learn to predictive modeling scenarios in other industries.…

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    Taschenbuch. Condición: Neu. Neuware -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 300 pp. Englisch.…

  • Idioma: Inglés

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    Paperback. Condición: new. Paperback. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Paperback. Condición: Brand New. 300 pages. 9.19x7.00x9.19 inches. In Stock. This item is printed on demand.

  • Idioma: Inglés

    Editorial: O'Reilly Media, 2026

    1098181115 / 9781098181116

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    Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE

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    Condición: Nuevo

    EUR 52,67

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    Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

  • Idioma: Inglés

    Editorial: O'Reilly Media, Sebastopol, 2026

    1098181115 / 9781098181116

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Paperback. Condición: new. Paperback. 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. Whether you're a complete beginner or you're interested in entering the burgeoning field of sports analytics, 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 dataDevelop, refine, and evaluate machine learning models, using Python for data analysisCarry out detailed analyses and research on soccer game predictions and betting strategies to surface valuable insightsApply 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…