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Data-driven approaches, particularly machine learning and data mining, are the main driving force of the current artificial intelligence technology. This book covers a wide variety of methods in machine learning and data mining, dividing them from a viewpoint of data types, which begin with rather simple vectors and end by graphs and also combination of different data types. This book describes standard techniques of machine learning and data mining for each data type, especially focusing on the relevance and difference among them. Also after explaining a series of machine learning methods for seven different data types, this book has a chapter for standard validation methods on empirical results obtained by applying machine learning methods to data. This book can be used for a variety of objectives, including an introductory textbook of studying machine learning and a (first step) book to start machine learning research, etc.