Deep Learning and XAI Techniques

Create interpretable AI models for transparent and

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Create interpretable AI models for transparent and

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This book explores the use of deep learning and explainable artificial intelligence (XAI) techniques for anomaly detection in various applications.

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"Deep Learning and XAI Techniques for Anomaly Detection" is a book written by Sridhar Alla, Soma Bandyopadhyay, and Kuan-Ching Li. It explores the use of deep learning and explainable artificial intelligence (XAI) techniques for anomaly detection in various applications. The book begins with an introduction to anomaly detection, its importance in various fields, and the challenges involved in detecting anomalies. It then delves into the use of deep learning techniques such as autoencoders, convolutional neural networks (CNNs), and recurrent neural networks (RNNs) for anomaly detection. The authors provide detailed explanations and code examples that make it easy for readers to follow along and apply what they learn.

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3yr ago

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