The book consists of three main parts:
· Introduction: The first chapter introduces big data, types of learning techniques, and the importance of pattern mining. The second chapter introduces the PAMI library, its organizational structure, installation, and usage.
· Pattern mining algorithms and examples: The following chapters present the state-of-the-art techniques for discovering user interest-based patterns in (1) transactional databases, (2) temporal databases, (3) quantitative databases, (4) uncertain databases, (5) sequential databases, and (6) graphs.
· Applications: The book concludes with several applications, where the predicted knowledge using TensorFlow and PyTorch was transformed into a database to discover future trends or patterns.
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