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Titlebook: Beginning Anomaly Detection Using Python-Based Deep Learning; Implement Anomaly De Suman Kalyan Adari,Sridhar Alla Book 2024Latest edition

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樓主: Jefferson
11#
發(fā)表于 2025-3-23 10:38:46 | 只看該作者
Book 2024Latest editionhine learning and deep learning, and how to implement multilayer perceptrons for supervised anomaly detection in both Keras and PyTorch. From here, the focus shifts to the applications of deep learning models for anomaly detection, including various types of autoencoders,?recurrent neural networks (
12#
發(fā)表于 2025-3-23 16:42:08 | 只看該作者
13#
發(fā)表于 2025-3-23 18:40:24 | 只看該作者
14#
發(fā)表于 2025-3-23 22:15:43 | 只看該作者
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發(fā)表于 2025-3-24 02:54:06 | 只看該作者
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發(fā)表于 2025-3-24 10:23:22 | 只看該作者
17#
發(fā)表于 2025-3-24 13:08:24 | 只看該作者
Introduction to Machine Learning,every modeling task you may come across, and they extend into deep learning modeling as well. This is a high-level theoretical introduction to machine learning, since the practical material and implementation of these machine learning principles will be covered in the subsequent chapters.
18#
發(fā)表于 2025-3-24 18:55:29 | 只看該作者
Introduction to Deep Learning,. These concepts will apply to the rest of the book and beyond. In the process, you will also implement a simple neural network model in both TensorFlow/Keras and PyTorch to perform supervised anomaly detection and serve as a gateway into learning how to model in these frameworks.
19#
發(fā)表于 2025-3-24 22:40:44 | 只看該作者
https://doi.org/10.1007/979-8-8688-0008-5Anamoly Detection; Deep Learning; Python; Keras; PyTorch; Novelty detection; Auto Encoders; Fraud Detection
20#
發(fā)表于 2025-3-25 00:30:52 | 只看該作者
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