ISBN: 9786207807062 - anomaly detection in log files: a comprehensive guide (11 resultados)

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Taschenbuch. Condición: Neu. Anomaly Detection in Log Files: A Comprehensive Guide | Tathagata Roy Chowdhury | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207807062 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 84 pp. Englisch.

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Anomaly Detection in Log Files: A Comprehensive Guide' by Tathagata Roy Chowdhury is an in-depth exploration of the methodologies and techniques used to identify anomalies in log files. This guide delves into the critical role of anomaly detection in enhancing cybersecurity and system monitoring by identifying unusual patterns and behaviors in data that deviate from the norm. The book begins with an introduction to AI and machine learning, providing a solid foundation for understanding the advanced techniques discussed later. Key chapters cover various aspects such as the architecture of distributed database management systems, data collection, data cleaning, and the creation of CSV files. The guide emphasizes the importance of data preparation, visualization, and the use of confusion matrices to evaluate model performance. By offering a detailed review of supervised methods and a thorough analysis of web servers, this book is an invaluable resource for both beginners and advanced practitioners in the field of anomaly detection.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Anomaly Detection in Log Files: A Comprehensive Guide' by Tathagata Roy Chowdhury is an in-depth exploration of the methodologies and techniques used to identify anomalies in log files. This guide delves into the critical role of anomaly detection in enhancing cybersecurity and system monitoring by identifying unusual patterns and behaviors in data that deviate from the norm. The book begins with an introduction to AI and machine learning, providing a solid foundation for understanding the advanced techniques discussed later. Key chapters cover various aspects such as the architecture of distributed database management systems, data collection, data cleaning, and the creation of CSV files. The guide emphasizes the importance of data preparation, visualization, and the use of confusion matrices to evaluate model performance. By offering a detailed review of supervised methods and a thorough analysis of web servers, this book is an invaluable resource for both beginners and advanced practitioners in the field of anomaly detection.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch.…