Isbn: 9781032030647 - predictive modelling for football analytics (chapman & hall/crc data science series) (17 resultados)

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. 1st edition NO-PA16APR2015-KAP.

Condición: New.

Condición: New.

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

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

Condición: New.

Hardback. Condición: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.…

Hardcover. Condición: Brand New. 272 pages. 9.18x6.12x9.21 inches. In Stock.

Hardback. Condición: New. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations.…

Hardcover. Condición: new. Hardcover. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations. Discusses well-known models and main computational tools for the football analytics domain. Introduces footBayes R package that accompanies the reader through all examples proposed in the book. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condición: new. Hardcover. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations. Discusses well-known models and main computational tools for the football analytics domain. Introduces footBayes R package that accompanies the reader through all examples proposed in the book. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condición: new. Hardcover. Predictive Modelling for Football Analytics discusses the most well-known models and the main computational tools for the football analytics domain. It further introduces the footBayes R package that accompanies the reader through all the examples proposed in the book. It aims to be both a practical guide and a theoretical foundation for students, data scientists, sports analysts, and football professionals who wish to understand and apply predictive modelling in a football context.Key FeaturesDiscusses various modelling strategies and predictive tools related to football analyticsIntroduces algorithms and computational tools to check the models, make predictions, and visualize the final resultsShowcases some guided examples through the use of the footBayes R package available on CRANWalks the reader through the full pipeline: from data collection and preprocessing, through exploratory analysis and feature engineering, to advanced modelling techniques and evaluationBridges the gap between raw football data and actionable insightsThis text is primarily for senior undergraduates, graduate students, and academic researchers in the fields of mathematics, statistics, and computer science willing to learn about the football analytics domain. Although technical in nature, the book is designed to be accessible to readers with a background in statistics, programming, or a strong interest in sports analytics. It is well-suited for use in academic courses on sports analytics, data science projects, or professional development within football clubs, agencies, and media organizations. Discusses well-known models and main computational tools for the football analytics domain. Introduces footBayes R package that accompanies the reader through all examples proposed in the book. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…