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Full Description
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.
Contents
Chapter 1: Game Data Science: an Introduction
Chapter 2: Data Pre-Processing
Chapter 3: Introduction to Statistics and Probability Theory
Chapter 4: Data Abstraction
Chapter 5: Visual Analytics of Game Data
Chapter 6: Clustering Methods in Game Data Science
Chapter 7: Supervised Learning in Game Data Science
Chapter 8: Model Evaluation and Validation
Chapter 9: Neural Networks
Chapter 10: Sequence Analysis of Game Data
Chapter 11: Advanced Sequence Analysis
Chapter 12: Social Network Analysis
Chapter 13: Conclusions and Final Remarks
