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Beginning Anomaly Detection Using PythonBased Deep Learning: With Keras and PyTorch,Used
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Utilize this easytofollow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semisupervised and unsupervised anomaly detection tasks.This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using ScikitLearn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semisupervised anomaly detection along with the basics of time seriesbased anomaly detection.By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to ScikitLearn and are able to create deep learning models in Keras and PyTorch.What You Will Learn Understand what anomaly detection is and why it is important in today's worldBecome familiar with statistical and traditional machine learning approaches to anomaly detection using ScikitLearnKnow the basics of deep learning in Python using Keras and PyTorchBe aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and moreApply deep learning to semisupervised and unsupervised anomaly detectionWho This Book Is ForData scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection
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