Football Analytics With Python R

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Football Analytics with Python & R

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Author : Eric A. Eager
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492099597
Total Pages : 352 pages
Book Rating : 4.4/5 (92 download)

Book Synopsis Football Analytics with Python & R by : Eric A. Eager

Download or read book Football Analytics with Python & R written by Eric A. Eager and published by "O'Reilly Media, Inc.". This book was released on 2023-08-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more

Sports Analytics and Data Science

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Author : Thomas W. Miller
Publisher : FT Press
ISBN 13 : 0133887413
Total Pages : 576 pages
Book Rating : 4.1/5 (338 download)

Book Synopsis Sports Analytics and Data Science by : Thomas W. Miller

Download or read book Sports Analytics and Data Science written by Thomas W. Miller and published by FT Press. This book was released on 2015-11-18 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This up-to-the-minute reference will help you master all three facets of sports analytics — and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations–not complex math. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business.

Football Analytics with Python & R

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Author : Eric A. Eager
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492099589
Total Pages : 361 pages
Book Rating : 4.4/5 (92 download)

Book Synopsis Football Analytics with Python & R by : Eric A. Eager

Download or read book Football Analytics with Python & R written by Eric A. Eager and published by "O'Reilly Media, Inc.". This book was released on 2023-08-15 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more

Behavioral Data Analysis with R and Python

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Author : Florent Buisson
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492061344
Total Pages : 361 pages
Book Rating : 4.4/5 (92 download)

Book Synopsis Behavioral Data Analysis with R and Python by : Florent Buisson

Download or read book Behavioral Data Analysis with R and Python written by Florent Buisson and published by "O'Reilly Media, Inc.". This book was released on 2021-06-15 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Data Analytics in Football

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Author : Daniel Memmert
Publisher : Routledge
ISBN 13 : 1351210149
Total Pages : 247 pages
Book Rating : 4.3/5 (512 download)

Book Synopsis Data Analytics in Football by : Daniel Memmert

Download or read book Data Analytics in Football written by Daniel Memmert and published by Routledge. This book was released on 2018-05-30 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics in Football provides students, researchers and coaches with a firm grounding in the principles of modern performance analysis. It offers an insight into the use of positional data, exploring how it can be collected, modelled, analysed and interpreted. Introducing cutting-edge methods, the book challenges long-held assumptions and encourages a new way of thinking about football analysis. Based on data collected from the German Bundesliga and the UEFA Champions League, the book seeks to define the role of positional data in football match analysis by exploring topics such as: What is positional data analysis and how did it emerge from conventional match analysis? How can positional data be collected and which technologies can be used? What are the benefits of a data-driven approach to decision making in football? What Key Performance Indicators based on positional data should be used? How can traditional match analysis be complemented by using positional data and advanced KPIs? How can these new methods evolve in the future? Accessibly written, packed full of examples from elite football and supplemented with expert interviews (Ralf Rangnick, Urs Siegenthaler and others), Data Analytics in Football is a thought-provoking, rigorously evidence-based guide to the use of data analytics in football performance analysis. As such, it is a vital resource for any student, researcher or coach interested in performance analysis and skill acquisition, or anyone interested in football more generally.

Sports Analytics

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Author : Benjamin C. Alamar
Publisher : Columbia University Press
ISBN 13 : 023155589X
Total Pages : 219 pages
Book Rating : 4.2/5 (315 download)

Book Synopsis Sports Analytics by : Benjamin C. Alamar

Download or read book Sports Analytics written by Benjamin C. Alamar and published by Columbia University Press. This book was released on 2024-05-28 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data and analytics have the potential to provide sports organizations with a competitive advantage both on and off the field. Yet even as the use of analytics in sports has become commonplace, teams regularly find themselves making big investments without significant payoff. This book is a practical, nontechnical guide to incorporating sports data into decision making, giving leaders the knowledge they need to maximize their organization’s investment in analytics. Benjamin C. Alamar—a leading expert who has built high-performing analytics groups—surveys the current state of the use of data in sports, including both specifics around the tools and how to deploy them most effectively. Sports Analytics offers a clear, easily digestible overview of data management, statistical models, and information systems and a detailed understanding of their vast possibilities. It walks readers through the essentials of understanding the value of different types of data and strategies for building and managing an analytics team. Throughout, Alamar illustrates the value of analytics with real-world examples and case studies from both the sports and business sides. Sports Analytics has guided a range of sports professionals to success since its original publication in 2013. This second edition adds examples and strategies that focus on using data on the business side of a sports organization, provides concrete strategies for incorporating different types of data into decision making, and updates all discussions for the rapid technological developments of the last decade.

Basketball Data Science

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Author : Paola Zuccolotto
Publisher : CRC Press
ISBN 13 : 0429894260
Total Pages : 245 pages
Book Rating : 4.4/5 (298 download)

Book Synopsis Basketball Data Science by : Paola Zuccolotto

Download or read book Basketball Data Science written by Paola Zuccolotto and published by CRC Press. This book was released on 2020-01-03 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball Presents tools for modelling graphs and figures to visualize the data Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case Provides the source code and data so readers can do their own analyses on NBA teams and players

Python and R for the Modern Data Scientist

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Author : Rick J. Scavetta
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492093378
Total Pages : 199 pages
Book Rating : 4.4/5 (92 download)

Book Synopsis Python and R for the Modern Data Scientist by : Rick J. Scavetta

Download or read book Python and R for the Modern Data Scientist written by Rick J. Scavetta and published by "O'Reilly Media, Inc.". This book was released on 2021-06-22 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together

Test-Driven Development with Python

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Author : Harry Percival
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491958650
Total Pages : 624 pages
Book Rating : 4.4/5 (919 download)

Book Synopsis Test-Driven Development with Python by : Harry Percival

Download or read book Test-Driven Development with Python written by Harry Percival and published by "O'Reilly Media, Inc.". This book was released on 2017-08-02 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques. If you’re ready to take your Python skills to the next level, this book—updated for Python 3.6—clearly demonstrates how TDD encourages simple designs and inspires confidence. Dive into the TDD workflow, including the unit test/code cycle and refactoring Use unit tests for classes and functions, and functional tests for user interactions within the browser Learn when and how to use mock objects, and the pros and cons of isolated vs. integrated tests Test and automate your deployments with a staging server Apply tests to the third-party plugins you integrate into your site Run tests automatically by using a Continuous Integration environment Use TDD to build a REST API with a front-end Ajax interface

Data Science and Analytics (with Python, R and SPSS Programming)

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Author : V.K. Jain
Publisher : KHANNA PUBLISHING HOUSE
ISBN 13 : 9386173670
Total Pages : 276 pages
Book Rating : 4.3/5 (861 download)

Book Synopsis Data Science and Analytics (with Python, R and SPSS Programming) by : V.K. Jain

Download or read book Data Science and Analytics (with Python, R and SPSS Programming) written by V.K. Jain and published by KHANNA PUBLISHING HOUSE. This book was released on with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book has been written completely as per AICTE recommended syllabus on "Data Sciences". SALIENT FEATURES OF THE BOOK: Explains how data is collected, managed and stored for data science. With complete courseware for understand the key concepts in data science including their real-world applications and the toolkit used by data scientists. Implement data collection and management. Provided with state of the arts subjectwise. With all required tutorials on R, Python and Bokeh, Anaconda, IBM SPSS-21 and Matplotlib.

Big Data Analytics with R

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Author : Simon Walkowiak
Publisher : Packt Publishing Ltd
ISBN 13 : 1786463725
Total Pages : 498 pages
Book Rating : 4.7/5 (864 download)

Book Synopsis Big Data Analytics with R by : Simon Walkowiak

Download or read book Big Data Analytics with R written by Simon Walkowiak and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.

Text Analytics with Python

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Author : Dipanjan Sarkar
Publisher : Apress
ISBN 13 : 1484223888
Total Pages : 397 pages
Book Rating : 4.4/5 (842 download)

Book Synopsis Text Analytics with Python by : Dipanjan Sarkar

Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2016-11-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Practical Statistics for Data Scientists

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Author : Peter Bruce
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491952911
Total Pages : 395 pages
Book Rating : 4.4/5 (919 download)

Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce

Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

See the First Steps: Football Analytics

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Author : Rodney Paul
Publisher :
ISBN 13 : 9781735524009
Total Pages : 150 pages
Book Rating : 4.5/5 (24 download)

Book Synopsis See the First Steps: Football Analytics by : Rodney Paul

Download or read book See the First Steps: Football Analytics written by Rodney Paul and published by . This book was released on 2020-08-15 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: See the First Steps: Football Analytics offers an introduction to the exciting world of charts and statistics surrounding the hot topic of analytics for the sport of football. Using NFL data from Pro Football Reference and Microsoft Excel Software, readers are introduced to a wide range of basic and advanced statistics, statistical concepts, and a variety of charts for data visualization.For teen readers, central concepts covered on the SAT, ACT, and in AP Statistics are noted in the book, along with hands-on experience computing measures of central tendency and dispersion, and plotting numerous charts illustrating league leaders, great individual performances, and relationships between NFL statistics from the 2019 season. For adults, the book provides a refresher on statistics in addition to building skills using charts in Excel. These proficiencies are great for analysis of the NFL and other sports and also provide valuable general abilities which are transferrable to work-related reports and presentations. See the First Steps: Football Analytics provides the means to share your love for the sport of football, while building valuable skills for young and old alike and offers the opportunity to work together as family and/or friends to enhance your love for the sport of football. The end goal is to provide a framework where you can do your own analytics of NFL players and teams to deepen your understanding and enjoyment of the game.

Practical Data Science with R

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Author : Nina Zumel
Publisher : Manning Publications
ISBN 13 : 9781617291562
Total Pages : 416 pages
Book Rating : 4.2/5 (915 download)

Book Synopsis Practical Data Science with R by : Nina Zumel

Download or read book Practical Data Science with R written by Nina Zumel and published by Manning Publications. This book was released on 2014-04-10 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics. Practical Data Science with R shows you how to apply the R programming language and useful statistical techniques to everyday business situations. Using examples from marketing, business intelligence, and decision support, it shows you how to design experiments (such as A/B tests), build predictive models, and present results to audiences of all levels. This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed. What's Inside Data science for the business professional Statistical analysis using the R language Project lifecycle, from planning to delivery Numerous instantly familiar use cases Keys to effective data presentations About the Authors Nina Zumel and John Mount are cofounders of a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at win-vector.com. Table of Contents PART 1 INTRODUCTION TO DATA SCIENCE The data science process Loading data into R Exploring data Managing data PART 2 MODELING METHODS Choosing and evaluating models Memorization methods Linear and logistic regression Unsupervised methods Exploring advanced methods PART 3 DELIVERING RESULTS Documentation and deployment Producing effective presentations

Sport Analytics

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Author : John Wolohan
Publisher :
ISBN 13 : 9781792453977
Total Pages : 277 pages
Book Rating : 4.4/5 (539 download)

Book Synopsis Sport Analytics by : John Wolohan

Download or read book Sport Analytics written by John Wolohan and published by . This book was released on 2021-10-30 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides readers with an analytical foundation required to do sport analytics and an overview of the canonical methods in sport analytics. To achieve the methods simultaneously, the book introduces the most important topics in sport analytics and teaches the practical and theoretical considerations.

Statistical Sports Models in Excel

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Author : Andrew Mack
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.6/5 (182 download)

Book Synopsis Statistical Sports Models in Excel by : Andrew Mack

Download or read book Statistical Sports Models in Excel written by Andrew Mack and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: