Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data
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Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data
Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data
Stavka #: 267647665

Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data

Stavka #: 267647665

€ 58

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  • 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 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
Publisher O'Reilly Media
Publication date June 15, 2026
Edition 1st
Language English
File size 4.4 MB
Enhanced typesetting Enabled
X-Ray Not Enabled
Word Wise Not Enabled
Print length 538 pages
ISBN-13 978-1098181079
Page Flip Enabled
Item Weight1.5 lbs (680 grams)

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Soccer Analytics with Machine Learning: Learning Predictive Modeling Techniques with Sports Data

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