Magy Seif El-Nasr is a Professor of Computational Media and Vice Chair of Serious Games program at University of California at Santa Cruz, where she also directs the Game User Interaction and Intelligence (GUII) Lab. Dr. Seif El-Nasr earned her Ph.D. degree from Northwestern University in Computer Science. Her work is internationally known and cited in several game industry books. Additionally, she has received several awards and recognition within the game research community.Truong-Huy Nguyen is currently working at Google as a Software Engineer. Before making the move to the tech industry, he was an assistant professor at the Department of Computer and Information Science at Fordham University, New York, NY. He received his PhD in Computer Science from the National University of Singapore. His research focuses on discovering how humans make decisions and form strategies and tactics from behavioral data, as well as building experimental and practical applications to leverage such insights. His research work lies at the cross-junction of machine learning, artificial intelligence, and behavior analytics, with favorite applications being games and robotics.Dr. Alessandro Canossa has been straddling between the game industry and academia for many years. He has been Assistant Professor at the IT University of Copenhagen, Associate Professor at Northeastern University in Boston and he's now Professor at the Royal Danish Academy of Fine Arts. In his research, he employs psychological theories of personality, perception, motivation and emotion to design games with the purpose of investigating individual differences in behavior among users of digital entertainment. He's now involved with Modl.AI, a company providing AI services to the game industry, where he's exploring how to triangulate data-driven insights with surveys and lab observations to advance the field of predictive analytics.Anders Drachen, PhD, is Professor at the University of York and Communications Director at the Department of Computer Science. He is co-director of the Digital Creativity Labs (digitalcreativity.ac.uk/), a UK Digital Economy Hub and World Centre for Excellence. He is recognized as one of the world's most influential people in business intelligence in the Creative industries, and a core innovator in the domain with 140+ publications across game analytics and games user research. His work has assisted major international game publishers, as well as SMEs, make better decisions based on their data.

Game Data Science describes practical techniques to analyze user data, which can be used to drive decision-making at multiple levels. Analyzing user game data can offer designers and publishers useful insights that inform decision-making processes from the very early stages of game design, through the marketing process, to potential patches and updates.

• 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

Magy Seif El-Nasr is a Professor of Computational Media and Vice Chair of Serious Games program at University of California at Santa Cruz, where she also directs the Game User Interaction and Intelligence (GUII) Lab. Dr. Seif El-Nasr earned her Ph.D. degree from Northwestern University in Computer Science. Her work is internationally known and cited in several game industry books. Additionally, she has received several awards and recognition within the game research community.Truong-Huy Nguyen is currently working at Google as a Software Engineer. Before making the move to the tech industry, he was an assistant professor at the Department of Computer and Information Science at Fordham University, New York, NY. He received his PhD in Computer Science from the National University of Singapore. His research focuses on discovering how humans make decisions and form strategies and tactics from behavioral data, as well as building experimental and practical applications to leverage such insights. His research work lies at the cross-junction of machine learning, artificial intelligence, and behavior analytics, with favorite applications being games and robotics.Dr. Alessandro Canossa has been straddling between the game industry and academia for many years. He has been Assistant Professor at the IT University of Copenhagen, Associate Professor at Northeastern University in Boston and he's now Professor at the Royal Danish Academy of Fine Arts. In his research, he employs psychological theories of personality, perception, motivation and emotion to design games with the purpose of investigating individual differences in behavior among users of digital entertainment. He's now involved with Modl.AI, a company providing AI services to the game industry, where he's exploring how to triangulate data-driven insights with surveys and lab observations to advance the field of predictive analytics.Anders Drachen, PhD, is Professor at the University of York and Communications Director at the Department of Computer Science. He is co-director of the Digital Creativity Labs (digitalcreativity.ac.uk/), a UK Digital Economy Hub and World Centre for Excellence. He is recognized as one of the world's most influential people in business intelligence in the Creative industries, and a core innovator in the domain with 140+ publications across game analytics and games user research. His work has assisted major international game publishers, as well as SMEs, make better decisions based on their data.

Game Data Science describes practical techniques to analyze user data, which can be used to drive decision-making at multiple levels. Analyzing user game data can offer designers and publishers useful insights that inform decision-making processes from the very early stages of game design, through the marketing process, to potential patches and updates.

• 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

Magy Seif El-Nasr is a Professor of Computational Media and Vice Chair of Serious Games program at University of California at Santa Cruz, where she also directs the Game User Interaction and Intelligence (GUII) Lab. Dr. Seif El-Nasr earned her Ph.D. degree from Northwestern University in Computer Science. Her work is internationally known and cited in several game industry books. Additionally, she has received several awards and recognition within the game research community.Truong-Huy Nguyen is currently working at Google as a Software Engineer. Before making the move to the tech industry, he was an assistant professor at the Department of Computer and Information Science at Fordham University, New York, NY. He received his PhD in Computer Science from the National University of Singapore. His research focuses on discovering how humans make decisions and form strategies and tactics from behavioral data, as well as building experimental and practical applications to leverage such insights. His research work lies at the cross-junction of machine learning, artificial intelligence, and behavior analytics, with favorite applications being games and robotics.Dr. Alessandro Canossa has been straddling between the game industry and academia for many years. He has been Assistant Professor at the IT University of Copenhagen, Associate Professor at Northeastern University in Boston and he's now Professor at the Royal Danish Academy of Fine Arts. In his research, he employs psychological theories of personality, perception, motivation and emotion to design games with the purpose of investigating individual differences in behavior among users of digital entertainment. He's now involved with Modl.AI, a company providing AI services to the game industry, where he's exploring how to triangulate data-driven insights with surveys and lab observations to advance the field of predictive analytics.Anders Drachen, PhD, is Professor at the University of York and Communications Director at the Department of Computer Science. He is co-director of the Digital Creativity Labs (digitalcreativity.ac.uk/), a UK Digital Economy Hub and World Centre for Excellence. He is recognized as one of the world's most influential people in business intelligence in the Creative industries, and a core innovator in the domain with 140+ publications across game analytics and games user research. His work has assisted major international game publishers, as well as SMEs, make better decisions based on their data.

Game Data Science describes practical techniques to analyze user data, which can be used to drive decision-making at multiple levels. Analyzing user game data can offer designers and publishers useful insights that inform decision-making processes from the very early stages of game design, through the marketing process, to potential patches and updates.

• 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