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| data science in gaming: Game Data Science Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, Anders Drachen, 2021 Game Data Science delivers a thorough introduction to this new domain and serves as a definitive guide to the methods and practices of computer science, analytics, and data science as applied to video games. It is the ideal resource for professional learners and students seeking to understand how data science is used within the game development and production cycle, as well as within the interdisciplinary field of games research. -- back cover. |
| data science in gaming: Data Analytics Applications in Gaming and Entertainment Günter Wallner, 2019-07-11 The last decade has witnessed the rise of big data in game development as the increasing proliferation of Internet-enabled gaming devices has made it easier than ever before to collect large amounts of player-related data. At the same time, the emergence of new business models and the diversification of the player base have exposed a broader potential audience, which attaches great importance to being able to tailor game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques, as they offer new opportunities for deriving actionable insights to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation. By now, data mining and analytics have become vital components of game development. The amount of work being done in this area nowadays makes this an ideal time to put together a book on this subject. Data Analytics Applications in Gaming and Entertainment seeks to provide a cross section of current data analytics applications in game production. It is intended as a companion for practitioners, academic researchers, and students seeking knowledge on the latest practices in game data mining. The chapters have been chosen in such a way as to cover a wide range of topics and to provide readers with a glimpse at the variety of applications of data mining in gaming. A total of 25 authors from industry and academia have contributed 12 chapters covering topics such as player profiling, approaches for analyzing player communities and their social structures, matchmaking, churn prediction and customer lifetime value estimation, communication of analytical results, and visual approaches to game analytics. This book’s perspectives and concepts will spark heightened interest in game analytics and foment innovative ideas that will advance the exciting field of online gaming and entertainment. |
| data science in gaming: Game Analytics Magy Seif El-Nasr, Anders Drachen, Alessandro Canossa, 2013-03-30 Developing a successful game in today’s market is a challenging endeavor. Thousands of titles are published yearly, all competing for players’ time and attention. Game analytics has emerged in the past few years as one of the main resources for ensuring game quality, maximizing success, understanding player behavior and enhancing the quality of the player experience. It has led to a paradigm shift in the development and design strategies of digital games, bringing data-driven intelligence practices into the fray for informing decision making at operational, tactical and strategic levels. Game Analytics - Maximizing the Value of Player Data is the first book on the topic of game analytics; the process of discovering and communicating patterns in data towards evaluating and driving action, improving performance and solving problems in game development and game research. Written by over 50 international experts from industry and research, it covers a comprehensive range of topics across more than 30 chapters, providing an in-depth discussion of game analytics and its practical applications. Topics covered include monetization strategies, design of telemetry systems, analytics for iterative production, game data mining and big data in game development, spatial analytics, visualization and reporting of analysis, player behavior analysis, quantitative user testing and game user research. This state-of-the-art volume is an essential source of reference for game developers and researchers. Key takeaways include: Thorough introduction to game analytics; covering analytics applied to data on players, processes and performance throughout the game lifecycle. In-depth coverage and advice on setting up analytics systems and developing good practices for integrating analytics in game-development and -management. Contributions by leading researchers and experienced professionals from the industry, including Ubisoft, Sony, EA, Bioware, Square Enix, THQ, Volition, and PlayableGames. Interviews with experienced industry professionals on how they use analytics to create hit games. |
| data science in gaming: Entertainment Science Thorsten Hennig-Thurau, Mark B. Houston, 2018-08-01 The entertainment industry has long been dominated by legendary screenwriter William Goldman’s “Nobody-Knows-Anything” mantra, which argues that success is the result of managerial intuition and instinct. This book builds the case that combining such intuition with data analytics and rigorous scholarly knowledge provides a source of sustainable competitive advantage – the same recipe for success that is behind the rise of firms such as Netflix and Spotify, but has also fueled Disney’s recent success. Unlocking a large repertoire of scientific studies by business scholars and entertainment economists, the authors identify essential factors, mechanisms, and methods that help a new entertainment product succeed. The book thus offers a timely alternative to “Nobody-Knows” decision-making in the digital era: while coupling a good idea with smart data analytics and entertainment theory cannot guarantee a hit, it systematically and substantially increases the probability of success in the entertainment industry. Entertainment Science is poised to inspire fresh new thinking among managers, students of entertainment, and scholars alike. Thorsten Hennig-Thurau and Mark B. Houston – two of our finest scholars in the area of entertainment marketing – have produced a definitive research-based compendium that cuts across various branches of the arts to explain the phenomena that provide consumption experiences to capture the hearts and minds of audiences. Morris B. Holbrook, W. T. Dillard Professor Emeritus of Marketing, Columbia University Entertainment Science is a must-read for everyone working in the entertainment industry today, where the impact of digital and the use of big data can’t be ignored anymore. Hennig-Thurau and Houston are the scientific frontrunners of knowledge that the industry urgently needs. Michael Kölmel, media entrepreneur and Honorary Professor of Media Economics at University of Leipzig Entertainment Science’s winning combination of creativity, theory, and data analytics offers managers in the creative industries and beyond a novel, compelling, and comprehensive approach to support their decision-making. This ground-breaking book marks the dawn of a new Golden Age of fruitful conversation between entertainment scholars, managers, and artists. Allègre Hadida, Associate Professor in Strategy, University of Cambridge |
| data science in gaming: Games User Research Anders Drachen, Pejman Mirza-Babaei, Lennart E. Nacke, 2018 Games live and die commercially on the player experience. Games User Research is collectively the way we optimise the quality of the user experience (UX) in games, working with all aspects of a game from the mechanics and interface, visuals and art, interaction and progression, making sure every element works in concert and supports the game UX. This means that Games User Research is essential and integral to the production of games and to shape the experience of players. Today, Games User Research stands as the primary pathway to understanding players and how to design, build, and launch games that provide the right game UX. Until now, the knowledge in Games User Research and Game UX has been fragmented and there were no comprehensive, authoritative resources available. This book bridges the current gap of knowledge in Games User Research, building the go-to resource for everyone working with players and games or other interactive entertainment products. It is accessible to those new to Games User Research, while being deeply comprehensive and insightful for even hardened veterans of the game industry. In this book, dozens of veterans share their wisdom and best practices on how to plan user research, obtain the actionable insights from users, conduct user-centred testing, which methods to use when, how platforms influence user research practices, and much, much more. |
| data science in gaming: Sports Analytics and Data Science Thomas W. Miller, 2015-11-18 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. |
| data science in gaming: Data Analytics Applications in Gaming and Entertainment Günter Wallner, 2019 |
| data science in gaming: Game Data Science Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, Anders Drachen, 2021-09-30 Game data science, defined as the practice of deriving insights from game data, has created a revolution in the multibillion-dollar games industry - informing and enhancing production, design, and development processes. Almost all game companies and academics have now adopted some type of game data science, every tool utilized by game developers allows collecting data from games, yet there has been no definitive resource for academics and professionals in this rapidly developing sector until now. Games Data Science delivers an excellent introduction to this new domain and provides the definitive guide to methods and practices of computer science, analytics, and data science as applied to video games. It is the ideal resource for academic students and professional learners seeking to understand how data science is used within the game development and production cycle, as well as within the interdisciplinary field of games research. Organized into chapters that integrate laboratory and game data examples, this book provides a unique resource to train and educate both industry professionals and academics about the use of game data science, with practical exercises and examples on how such processes are implemented and used in academia and industry, interweaving theoretical learning with practical application throughout. |
| data science in gaming: Gaming the Metrics Mario Biagioli, Alexandra Lippman, 2020-01-28 How the increasing reliance on metrics to evaluate scholarly publications has produced new forms of academic fraud and misconduct. The traditional academic imperative to “publish or perish” is increasingly coupled with the newer necessity of “impact or perish”—the requirement that a publication have “impact,” as measured by a variety of metrics, including citations, views, and downloads. Gaming the Metrics examines how the increasing reliance on metrics to evaluate scholarly publications has produced radically new forms of academic fraud and misconduct. The contributors show that the metrics-based “audit culture” has changed the ecology of research, fostering the gaming and manipulation of quantitative indicators, which lead to the invention of such novel forms of misconduct as citation rings and variously rigged peer reviews. The chapters, written by both scholars and those in the trenches of academic publication, provide a map of academic fraud and misconduct today. They consider such topics as the shortcomings of metrics, the gaming of impact factors, the emergence of so-called predatory journals, the “salami slicing” of scientific findings, the rigging of global university rankings, and the creation of new watchdogs and forensic practices. |
| data science in gaming: Learning by Playing Fran Blumberg, 2014 There is a growing recognition in the learning sciences that video games can no longer be seen as impediments to education, but rather, they can be developed to enhance learning. Educational and developmental psychologists, education researchers, media psychologists, and cognitive psychologists are now joining game designers and developers in seeking out new ways to use video game play in the classroom. In Learning by Playing, a diverse group of contributors provide perspectives on the most current thinking concerning the ramifications of leisure video game play for academic classroom learning. The first section of the text provides foundational understanding of the cognitive skills and content knowledge that children and adolescents acquire and refine during video game play. The second section explores game features that captivate and promote skills development among game players. The subsequent sections discuss children and adolescents' learning in the context of different types of games and the factors that contribute to transfer of learning from video game play to the classroom. These chapters then form the basis for the concluding section of the text: a specification of the most appropriate research agenda to investigate the academic potential of video game play, particularly using those games that child and adolescent players find most compelling. Contributors include researchers in education, learning sciences, and cognitive and developmental psychology, as well as instructional design researchers. |
| data science in gaming: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| data science in gaming: Artificial Intelligence and Games Georgios N. Yannakakis, Julian Togelius, 2018-02-17 This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading. |
| data science in gaming: Emerging Technologies and Applications for Cloud-Based Gaming Krishna, P. Venkata, 2016-07-13 Online gaming is widely popular and gaining more user attention every day. Computer game industries have made considerable growth in terms of design and development, but the scarcity of hardware resources at player or client side is a major pitfall for the latest high-end multimedia games. Cloud gaming is one proposed solution, allowing the end-user to play games using a variety of platforms with less demanding hardware requirements. Emerging Technologies and Applications for Cloud-Based Gaming explores the opportunities for the gaming industry through the integration of cloud computing. Focusing on design methodologies, fundamental architectures, and the end-user experience, this publication is an essential reference source for IT specialists, game developers, researchers, and graduate-level students. |
| data science in gaming: Data Scientist Pocket Guide Mohamed Sabri, 2021-06-24 Discover one of the most complete dictionaries in data science. KEY FEATURES ● Simplified understanding of complex concepts, terms, terminologies, and techniques. ● Combined glossary of machine learning, mathematics, and statistics. ● Chronologically arranged A-Z keywords with brief description. DESCRIPTION This pocket guide is a must for all data professionals in their day-to-day work processes. This book brings a comprehensive pack of glossaries of machine learning, deep learning, mathematics, and statistics. The extensive list of glossaries comprises concepts, processes, algorithms, data structures, techniques, and many more. Each of these terms is explained in the simplest words possible. This pocket guide will help you to stay up to date of the most essential terms and references used in the process of data analysis and machine learning. WHAT YOU WILL LEARN ● Get absolute clarity on every concept, process, and algorithm used in the process of data science operations. ● Keep yourself technically strong and sound-minded during data science meetings. ● Strengthen your knowledge in the field of Big data and business intelligence. WHO THIS BOOK IS FOR This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science. TABLE OF CONTENTS 1. Chapter one: A 2. Chapter two: B 3. Chapter three: C 4. Chapter four: D 5. Chapter five: E 6. Chapter six: F 7. Chapter seven: G 8. Chapter eight: H 9. Chapter nine: I 10. Chapter ten: J 11. Chapter 11: K 12. Chapter 12: L 13. Chapter 13: M 14. Chapter 14: N 15. Chapter 15: O 16. Chapter 16: P 17. Chapter 17: Q 18. Chapter 18: R 19. Chapter 19 : S 20. Chapter 20 : T 21. Chapter 21 : U 22. Chapter 22 : V 23. Chapter 23: W 24. Chapter 24: X 25. Chapter 25: Y 26. Chapter 26 : Z |
| data science in gaming: AI for Game Developers David M. Bourg, Glenn Seemann, 2004 From the author of Physics for Game Developers, comes a new, non-threatening introduction to the complex subject of game programming. |
| data science in gaming: The Psychology of Video Games Celia Hodent, 2020-10-07 What impact can video games have on us as players? How does psychology influence video game creation? Why do some games become cultural phenomena? The Psychology of Video Games introduces the curious reader to the relationship between psychology and video games from the perspective of both game makers and players. Assuming no specialist knowledge, this concise, approachable guide is a starter book for anyone intrigued by what makes video games engaging and what is their psychological impact on gamers. It digests the research exploring the benefits gaming can have on players in relation to education and healthcare, considers the concerns over potential negative impacts such as pathological gaming, and concludes with some ethics considerations. With gaming being one of the most popular forms of entertainment today, The Psychology of Video Games shows the importance of understanding the human brain and its mental processes to foster ethical and inclusive video games. |
| data science in gaming: Data Science Thinking Longbing Cao, 2018-08-17 This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective. |
| data science in gaming: Analyzing Future Applications of AI, Sensors, and Robotics in Society Thomas Heinrich Musiolik, Adrian David Cheok, 2020 This book explores the future challenges and hidden potentials of the application of artificial intelligence, sensors, and robotics in society-- |
| data science in gaming: Core Techniques and Algorithms in Game Programming Daniel Sánchez-Crespo Dalmau, 2004 To even try to keep pace with the rapid evolution of game development, you need a strong foundation in core programming techniques-not a hefty volume on one narrow topic or one that devotes itself to API-specific implementations. Finally, there's a guide that delivers! As a professor at the Spanish university that offered that country's first master's degree in video game creation, author Daniel Sanchez-Crespo recognizes that there's a core programming curriculum every game designer should be well versed in-and he's outlined it in these pages! By focusing on time-tested coding techniques-and providing code samples that use C++, and the OpenGL and DirectX APIs-Daniel has produced a guide whose shelf life will extend long beyond the latest industry trend. Code design, data structures, design patterns, AI, scripting engines, 3D pipelines, texture mapping, and more: They're all covered here-in clear, coherent fashion and with a focus on the essentials that will have you referring back to this volume for years to come. |
| data science in gaming: Advances in Computer Games Mark H.M. Winands, H. Jaap van den Herik, Walter A. Kosters, 2017-12-21 This book constitutes the refereed conference proceedings of the 15th International Conference, ACG 2017, held in Leiden, The Netherlands, in July 2017.The 19 revised full papers were selected from 23 submissions and cover a wide range of computer games. They are grouped in four classes according to the order of publication: games and puzzles, go and chess, machine learning and MCTS, and gaming. |
| data science in gaming: Data Science from Scratch Steven Cooper, 2018-08-10 ★☆If you are looking to start a new career that is in high demand, then you need to continue reading!★☆ Data scientists are changing the way big data is used in different institutions. Big data is everywhere, but without the right person to interpret it, it means nothing. So where do business find these people to help change their business? You could be that person! It has become a universal truth that businesses are full of data. With the use of big data, the US healthcare could reduce their health-care spending by $300 billion to $450 billion. It can easily be seen that the value of big data lies in the analysis and processing of that data, and that's where data science comes in. ★★ Grab your copy today and learn ★★ ♦ In depth information about what data science is and why it is important. ♦ The prerequisites you will need to get started in data science. ♦ What it means to be a data scientist. ♦ The roles that hacking and coding play in data science. ♦ The different coding languages that can be used in data science. ♦ Why python is so important. ♦ How to use linear algebra and statistics. ♦ The different applications for data science. ♦ How to work with the data through munging and cleaning ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. As businesses and the internet change, so will data science. This means it's important to be flexible. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started in a new, ever growing, career, don't wait any longer. Scroll up and click the buy now button to get this book today! |
| data science in gaming: Data Engineering and Data Science Kukatlapalli Pradeep Kumar, Aynur Unal, Vinay Jha Pillai, Hari Murthy, M. Niranjanamurthy, 2023-10-03 DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library. |
| data science in gaming: Artificial Intelligence for Games Ian Millington, John Funge, 2018-12-14 Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques. Artificial Intelligence for Games - 2nd edition will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games). Key Features * The first comprehensive, professional tutorial and reference to implement true AI in games written by an engineer with extensive industry experience. * Walks through the entire development process from beginning to end. * Includes examples from over 100 real games, 10 in-depth case studies, and web site with sample code. |
| data science in gaming: Freemium Economics Eric Benjamin Seufert, 2013-12-27 Freemium Economics presents a practical, instructive approach to successfully implementing the freemium model into your software products by building analytics into product design from the earliest stages of development. Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deliver revenue can be challenging if you don't fully understand the impact that small changes can have on revenue. In this book, author Eric Seufert provides clear guidelines for using data and analytics through all stages of development to optimize your implementation of the freemium model. Freemium Economics de-mystifies the freemium model through an exploration of its core, data-oriented tenets, so that you can apply it methodically rather than hoping that conversion and revenue will naturally follow product launch. - Learn how to apply data science and big data principles in freemium product design and development to maximize conversion, boost retention, and deliver revenue - Gain a broad introduction to the conceptual economic pillars of freemium and a complete understanding of the unique approaches needed to acquire users and convert them from free to paying customers - Get practical tips and analytical guidance to successfully implement the freemium model - Understand the metrics and infrastructure required to measure the success of a freemium product and improve it post-launch - Includes a detailed explanation of the lifetime customer value (LCV) calculation and step-by-step instructions for implementing key performance indicators in a simple, universally-accessible tool like Excel |
| data science in gaming: Game Usability Katherine Isbister, Noah Schaffer, 2008-08-12 Computers used to be for geeks. And geeks were fine with dealing with a difficult and finicky interface--they liked this--it was even a sort of badge of honor (e.g. the Unix geeks). But making the interface really intuitive and useful--think about the first Macintosh computers--took computers far far beyond the geek crowd. The Mac made HCI (human c |
| data science in gaming: Recent Developments in Data Science and Intelligent Analysis of Information Oleg Chertov, Tymofiy Mylovanov, Yuriy Kondratenko, Janusz Kacprzyk, Vladik Kreinovich, Vadim Stefanuk, 2018-08-04 This book constitutes the proceedings of the XVIII International Conference on Data Science and Intelligent Analysis of Information (ICDSIAI'2018), held in Kiev, Ukraine on June 4-7, 2018. The conference series, which dates back to 2001 when it was known as the Workshop on Intelligent Analysis of Information, was renamed in 2008 to reflect the broadening of its scope and the composition of its organizers and participants. ICDSIAI'2018 brought together a large number of participants from numerous countries in Europe, Asia and the USA. The papers presented addressed novel theoretical developments in methods, algorithms and implementations for the broadly perceived areas of big data mining and intelligent analysis of data and information, representation and processing of uncertainty and fuzziness, including contributions on a range of applications in the fields of decision-making and decision support, economics, education, ecology, law, and various areas of technology. The book is dedicated to the memory of the conference founder, the late Professor Tetiana Taran, an outstanding scientist in the field of artificial intelligence whose research record, vision and personality have greatly contributed to the development of Ukrainian artificial intelligence and computer science. |
| data science in gaming: Data Pipelines Pocket Reference James Densmore, 2021-02-10 Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting |
| data science in gaming: Simulation and Gaming for Social Design Toshiyuki Kaneda, Ryoju Hamada, Terukazu Kumazawa, 2022-01-03 This book is a collection of research articles that deal with three aspects of simulation and gaming for social design: (1) Theory and methodology, including game system theory and agent-based modeling; (2) Sustainability, including global warming and the energy–food nexus);; and (3) Social entrepreneurship, including business, ethnic, and ethical understanding. The latter two especially form two major areas of clinical knowledge in contemporary life. Simulation and gaming, with its participatory approach, provides participants with a seamless integration of problem solving and education. It has been known as a tool for interdisciplinary communication since the 1960s, and now it is being developed to contribute to global society in the twenty-first century. This is the first book on simulation and gaming for social design that covers all aspects from the methodological foundations to practical examples in the fields of sustainability and social entrepreneurship. Regardless of the size of the problematics, societal system design involves (1) The visioning and conception aspects due to the long-term, overall nature of the goal; (2) Interdisciplinary thinking and communication for the exploration of new states of accommodation with technological systems; and (3) The “human dimension” aspect including education that must be dealt with, thus academic developments of simulation and gaming for social design as system thinking and practice methodologies are anticipated. Simulation and gaming has great potential for development as a tool to facilitate the transfer between theoretical and clinical knowledge. |
| data science in gaming: How To Be A Games User Researcher Steve Bromley, 2021-02-05 Love video games? Start your career making them better. Games user researchers run playtests to ensure games are understandable and enjoyable, and are a key part of making games that people love. The video games industry is full of passionate people who care about making fun experiences. If you love games, and want to make them better, consider a career in games user research. Drawing upon ten years of experience working on top games and helping people start their career in games How To Be A Games User Researcher is the essential guide on how to run professional quality playtest studies and get a job in the games industry. What's in the book? Discover How games development works and where research fits in How to plan, run, analyse and debrief professional quality playtests The importance of building relationships with game teams How to start a career in user research The skills required to excel at job interviews Who is this book for? This book is for: Students considering a career in games user research UX researchers looking to transition into games New games user researchers Academics studying games design, development, or HCI Game designers and developers looking to improve the quality of their playtests About the author Steve Bromley led research studies for many of PlayStation's top European games including Horizon: Zero Dawn, SingStar and the PlayStation VR launch lineup. He continues to work with games and VR studios to improve the player experience of their games. For the last five years, Steve Bromley has run a games user research mentoring scheme, which has partnered over one hundred students with more than fifty industry professionals from top companies such as Sony, EA, Valve, Ubisoft, and Microsoft, and helped many people get their first job in games. This book covers many of the topics that mentees have asked as they start their games user research career. |
| data science in gaming: Handbook of Research on Effective Electronic Gaming in Education Ferdig, Richard E., 2008-07-31 This book presents a framework for understanding games for educational purposes while providing a broader sense of current related research. This creative and advanced title is a must-have for those interested in expanding their knowledge of this exciting field of electronic gaming--Provided by publisher. |
| data science in gaming: Deep Learning and the Game of Go Kevin Ferguson, Max Pumperla, 2019-01-06 Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning |
| data science in gaming: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry Chkoniya, Valentina, 2021-06-25 The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students. |
| data science in gaming: Hands-On Deep Learning for Games Micheal Lanham, 2019-03-30 Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key FeaturesApply the power of deep learning to complex reasoning tasks by building a Game AIExploit the most recent developments in machine learning and AI for building smart gamesImplement deep learning models and neural networks with PythonBook Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning. What you will learnLearn the foundations of neural networks and deep learning.Use advanced neural network architectures in applications to create music, textures, self driving cars and chatbots. Understand the basics of reinforcement and DRL and how to apply it to solve a variety of problems.Working with Unity ML-Agents toolkit and how to install, setup and run the kit.Understand core concepts of DRL and the differences between discrete and continuous action environments.Use several advanced forms of learning in various scenarios from developing agents to testing games.Who this book is for This books is for game developers who wish to create highly interactive games by leveraging the power of machine and deep learning. No prior knowledge of machine learning, deep learning or neural networks is required this book will teach those concepts from scratch. A good understanding of Python is required. |
| data science in gaming: Data Science Pallavi Vijay Chavan, Parikshit N Mahalle, Ramchandra Mangrulkar, Idongesit Williams, 2022-08-15 This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful. |
| data science in gaming: Data Science Without Makeup Mikhail Zhilkin, 2021-11-01 Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players’ physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence. Why data science is hard, what pitfalls analysts and decision-makers fall into, and what everyone involved can do to give themselves a fighting chance—the book examines these and other questions with the skepticism of someone who has seen the sausage being made. Honest and direct, full of examples from real life, Data Science Without Makeup: A Guidebook for End-Users, Analysts and Managers will be of great interest to people who aspire to work with data, people who already work with data, and people who work with people who work with data—from students to professional researchers and from early-career to seasoned professionals. Mikhail Zhilkin is a data scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting. |
| data science in gaming: Game Theory and Behavior Jeffrey Carpenter, Andrea Robbett, 2022-12-06 An introduction to game theory that offers not only theoretical tools but also the intuition and behavioral insights to apply these tools to real-world situations. This introductory text on game theory provides students with both the theoretical tools to analyze situations through the logic of game theory and the intuition and behavioral insights to apply these tools to real-world situations. It is unique among game theory texts in offering a clear, formal introduction to standard game theory while incorporating evidence from experimental data and introducing recent behavioral models. Students will not only learn about incentives, how to represent situations as games, and what agents “should” do in these situations, but they will also be presented with evidence that either confirms the theoretical assumptions or suggests a way in which the theory might be updated. Features: Each chapter begins with a motivating example that can be run as an experiment and ends with a discussion of the behavior in the example. Parts I–IV cover the fundamental “nuts and bolts” of any introductory game theory course, including the theory of games, simple games with simultaneous decision making by players, sequential move games, and incomplete information in simultaneous and sequential move games. Parts V–VII apply the tools developed in previous sections to bargaining, cooperative game theory, market design, social dilemmas, and social choice and voting. Part VIII offers a more in-depth discussion of behavioral game theory models including evolutionary and psychological game theory. Supplemental material on the book’s website include solutions to end-of-chapter exercises, a manual for running each chapter’s experimental games using pencil and paper, and the oTree codes for running the games online. |
| data science in gaming: Examining the Evolution of Gaming and Its Impact on Social, Cultural, and Political Perspectives Valentine, Keri Duncan, Jensen, Lucas John, 2016-06-20 With complex stories and stunning visuals eliciting intense emotional responses, coupled with opportunities for self-expression and problem solving, video games are a powerful medium to foster empathy, critical thinking, and creativity in players. As these games grow in popularity, ambition, and technological prowess, they become a legitimate art form, shedding old attitudes and misconceptions along the way. Examining the Evolution of Gaming and Its Impact on Social, Cultural, and Political Perspectives asks whether videogames have the power to transform a player and his or her beliefs from a sociopolitical perspective. Unlike traditional forms of storytelling, videogames allow users to immerse themselves in new worlds, situations, and politics. This publication surveys the landscape of videogames and analyzes the emergent gaming that shifts the definition and cultural effects of videogames. This book is a valuable resource to game designers and developers, sociologists, students of gaming, and researchers in relevant fields. |
| data science in gaming: HTML5 Game Development For Dummies Andy Harris, 2013-04-08 Create games with graphics that pop for the web and mobile devices! HTML5 is the tool game developers and designers have been eagerly awaiting. It simplifies the job of creating graphically rich, interactive games for the Internet and mobile devices, and this easy-to-use guide simplifies the learning curve. Illustrated in full color, the book takes you step by step through the basics of HTML5 and how to use it to build interactive games with 2D graphics, video, database capability, and plenty of action. Learn to create sports and adventure games, pong games, board games, and more, for both mobile devices and the standard web. Learn to use the new HTML5 technology that makes it easier to create games with lots of action, colorful 2D graphics, and interactivity--for both the web and mobile devices Test and debug your games before deploying them Take advantage of how HTML5 allows for SQL-like data storage, which is especially valuable if you're not well versed in database management Explore creating games suitable for community activity and powerful, profitable games that require large amounts of data Whether you want to build games as a fun hobby or hope to launch a new career, this full-color guide covers everything you need to know to make the most of HTML5 for game design. |
| data science in gaming: Gaming AI George Gilder, 2020-10-15 Pointing to the triumph of artificial intelligence over unaided humans in everything from games such as chess and Go to vital tasks such as protein folding and securities trading, many experts uphold the theory of a singularity. This is the trigger point when human history ends and artificial intelligence prevails in an exponential cascade of self-replicating machines rocketing toward godlike supremacy in the universe. Gaming AI suggests that this belief is both dumb and self-defeating. Displaying a profound and crippling case of professional amnesia, the computer science establishment shows an ignorance of the most important findings of its own science, from Kurt Gödel's incompleteness to Alan Turing's oracle to Claude Shannon's entropy. Dabbling in quantum machines, these believers in machine transcendence defy the deepest findings of quantum theory. Claiming to create minds, they are clinically out of their minds. Despite the quasi-religious pretensions of techno-elites nobly saving the planet from their own devices, their faith in a techno-utopian singularity is a serious threat to real progress. An industry utterly dependent on human minds will not prosper by obsoleting both their customers and their creators. Gaming AI calls for a remedial immersion in the industry's own heroic history and an understanding of the actual science of their own human minds. |
| data science in gaming: AI for Games Ian Millington, 2021-11-15 What is artificial intelligence? How is artificial intelligence used in game development? Game development lives in its own technical world. It has its own idioms, skills, and challenges. That’s one of the reasons games are so much fun to work on. Each game has its own rules, its own aesthetic, and its own trade-offs, and the hardware it will run on keeps changing. AI for Games is designed to help you understand one element of game development: artificial intelligence (AI). |
A Brief Overview of Data Mining and Analytics in Games
Game analytics uses data mining techniques to discover patterns and to extract information from game-related data, especially player behavioral data. As it is often the case with new fields, the …
Data Analytics Applications in Gaming and Entertainment
In this chapter—taking a multidisciplinary approach combining media, cultural, and game studies—Apperley and Gandolfi discuss how achievements can be used as tools to enable a …
A data science approach to mitigating data challenges in …
This paper centers on a critical examination of methodological challenges encountered while working with citizen scientists from serious gaming concept, and it delves into implementing …
Data-Driven Game Development: Ethical Considerations
In recent years, the games industry has made a major move to-wards data-driven development, using data analytics and player modeling to inform design decisions. Data-driven techniques …
ANALYTICAL CASE STUDY OF CASINO AND RESORT - Dell
Analyzing individual player data to predict which games will be played, and when, as well as predicting casino winnings from that play in order to optimize game inventory and floor layout.
DataRPG: Improving student motivation in data science …
DataRPG: Improving student motivation in data science through gaming elements Azim Abdool, Daniel Ringis, Aniel Maharajh, Lynda Sirju and Hannah Abdool
Data Governance in Gaming Industry
layer data. As gaming companies collect and analyze vast amounts of data, questions arise about the boundaries and ethics of this data usage. This includes concerns about how data is …
Data Science In Gaming Industry - media.wickedlocal.com
Data science is no longer a luxury but a necessity for success in the modern gaming industry. By harnessing the power of data, developers can create more engaging, balanced, and profitable...
“Data-Centric Evaluation of Microtransactions: Analysing Their …
This study offers a data-driven evaluation of the impact of microtransactions on player persistence, engagement, and behaviour in online gaming. The results reveal that cosmetic …
Building a Data Lake Architecture for Gaming Applications
Data is the new oil fuelling all industrial segments, including gaming. Understanding user behavior, identifying trends and preferences, and analyzing games for problem-solving are …
Apache Spark in Riot Games: A Case Study on Data Processing …
Versatile data processing: Spark's support for various data formats, including structured (Spark SQL), semi-structured (Spark DataFrames), and unstructured (Spark Streaming), made it an …
Best Practices for Building a Data Lake on AWS for Games
This whitepaper provides an in-depth discussion of best practices for building a data lake on AWS for games. It aims to help game developers maximize the value of their player data to achieve …
Big Data and Marketing Analytics in Gaming ... - Marketing …
Mar 6, 2014 · We describe a marketing analytics system we developed in one industry gaming and gambling where transactional-level data on consumer play behavior along with targeted …
Sensors and Game Synchronization for Data Analysis in eSports
In particular, we demonstrate how to synchronize various sensors and ensure post synchronization, i.e. logged video, a so-called demo file, with the sensors data. Our …
Here’s How Big Data is an Advantage for Gaming Industry
Consumers are producing more data in online gaming than ever before. As the volume of data increasing at an exponentially faster rate, the need for big data is essential to satisfy end-user …
International Journal of Scientific Research in Science, …
MPI, Apache Spark and machine learning models enables gaming platforms to predict future system usage, process telemetry data fast and adapt to players’ actions. Therefore, while …
From eSports Data to Game Commentary: Datasets, Models, …
We first build a data-to-text dataset containing data records and game commentaries from the a popular eSports game, League of Legends. On this new dataset, we propose a hierarchical …
CONSISTENT GAMING SKILL DEMOGRAPHICS IN ACADEMIC …
2.1 Demographic Category Labels tent when it comes to how gaming skill should be labeled. Some researchers label the more experienced gamers as “hardcore” (Baumann et al., 2018; …
Game Science: Foundations and Perspectives - SAGE Journals
The contributions range from the linkages between game science and complex social systems design through gaming simulation, to gamification science, and game studies, focusing on the …
A Brief Overview of Data Mining and Analytics in Games
Game analytics uses data mining techniques to discover patterns and to extract information from game-related data, especially player behavioral data. As it is often the case with new fields, …
Game Analytics The Basic - University of British Columbia
d game research environment. Analytics is the process of discovering and communicating patterns in data, towards solving problems in business or conversely predictions for supporting …
Data Analytics Applications in Gaming and Entertainment
In this chapter—taking a multidisciplinary approach combining media, cultural, and game studies—Apperley and Gandolfi discuss how achievements can be used as tools to enable a …
A data science approach to mitigating data challenges in …
This paper centers on a critical examination of methodological challenges encountered while working with citizen scientists from serious gaming concept, and it delves into implementing …
Data-Driven Game Development: Ethical Considerations
In recent years, the games industry has made a major move to-wards data-driven development, using data analytics and player modeling to inform design decisions. Data-driven techniques …
ANALYTICAL CASE STUDY OF CASINO AND RESORT - Dell
Analyzing individual player data to predict which games will be played, and when, as well as predicting casino winnings from that play in order to optimize game inventory and floor layout.
DataRPG: Improving student motivation in data science …
DataRPG: Improving student motivation in data science through gaming elements Azim Abdool, Daniel Ringis, Aniel Maharajh, Lynda Sirju and Hannah Abdool
Data Governance in Gaming Industry
layer data. As gaming companies collect and analyze vast amounts of data, questions arise about the boundaries and ethics of this data usage. This includes concerns about how data is …
Data Science In Gaming Industry - media.wickedlocal.com
Data science is no longer a luxury but a necessity for success in the modern gaming industry. By harnessing the power of data, developers can create more engaging, balanced, and profitable...
“Data-Centric Evaluation of Microtransactions: Analysing Their …
This study offers a data-driven evaluation of the impact of microtransactions on player persistence, engagement, and behaviour in online gaming. The results reveal that cosmetic …
Building a Data Lake Architecture for Gaming Applications
Data is the new oil fuelling all industrial segments, including gaming. Understanding user behavior, identifying trends and preferences, and analyzing games for problem-solving are …
Apache Spark in Riot Games: A Case Study on Data …
Versatile data processing: Spark's support for various data formats, including structured (Spark SQL), semi-structured (Spark DataFrames), and unstructured (Spark Streaming), made it an …
Best Practices for Building a Data Lake on AWS for Games
This whitepaper provides an in-depth discussion of best practices for building a data lake on AWS for games. It aims to help game developers maximize the value of their player data to achieve …
Big Data and Marketing Analytics in Gaming ... - Marketing …
Mar 6, 2014 · We describe a marketing analytics system we developed in one industry gaming and gambling where transactional-level data on consumer play behavior along with targeted …
Sensors and Game Synchronization for Data Analysis in …
In particular, we demonstrate how to synchronize various sensors and ensure post synchronization, i.e. logged video, a so-called demo file, with the sensors data. Our …
Here’s How Big Data is an Advantage for Gaming Industry
Consumers are producing more data in online gaming than ever before. As the volume of data increasing at an exponentially faster rate, the need for big data is essential to satisfy end-user …
International Journal of Scientific Research in Science, …
MPI, Apache Spark and machine learning models enables gaming platforms to predict future system usage, process telemetry data fast and adapt to players’ actions. Therefore, while …
From eSports Data to Game Commentary: Datasets, Models, …
We first build a data-to-text dataset containing data records and game commentaries from the a popular eSports game, League of Legends. On this new dataset, we propose a hierarchical …
CONSISTENT GAMING SKILL DEMOGRAPHICS IN ACADEMIC …
2.1 Demographic Category Labels tent when it comes to how gaming skill should be labeled. Some researchers label the more experienced gamers as “hardcore” (Baumann et al., 2018; …
Game Science: Foundations and Perspectives - SAGE Journals
The contributions range from the linkages between game science and complex social systems design through gaming simulation, to gamification science, and game studies, focusing on the …
