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29.2 MB
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July 13, 2025, 11:34 a.m.
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(Last updated: Aug. 21, 2025, 10:14 a.m.)
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| ['Rage U. Hands-on Pattern Mining. Theory and Examples...Keras,...TensorFlow 2025.pdf'] | 0 bytes |
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SOURCE: Rage U. Hands-on Pattern Mining. Theory and Examples...Keras,...TensorFlow 2025
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MEDIAINFO
Textbook in PDF format Presents ample examples to illustrate the theoretical concepts. Provides Python codes to implement the concepts. Makes use of open-source software and real-world databases for practical purposes. This book introduces pattern mining by presenting various pattern mining techniques and giving hands-on experience with each technique. Pattern mining is a popular data mining technique with many real-world applications, and involves discovering all user interest-based patterns that may exist in a database. Several models and numerous algorithms were described in the literature to find these patterns in binary databases, quantitative databases, uncertain databases, and streams. Since the lack of a Python toolkit containing these algorithms has limited the wide adaptability of pattern-mining techniques, the author developed Pattern Mining (PAMI) Python library, which currently contains 80+ algorithms to discover useful patterns in transactional databases, temporal databases, quantitative databases, and graphs. 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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