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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Beginning Anomaly Detection Using Python-Based Deep Learning
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Beginning Anomaly Detection Using Python-Based Deep Learning
Suman Kalyan Adari, Sridhar Alla (Broschiert, Englisch)
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Beschreibung
This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book, you will learn how to use Keras and PyTorch in practical applications. It also introduces new… chapters on GANs and transformers to reflect the latest trends in deep learning. Beginning Anomaly Detection Using Python-Based Deep Learning begins with an introduction to anomaly detection, its importance, and its applications. It then covers core data science and machine learning modeling concepts before delving into traditional machine learning algorithms such as OC-SVM and Isolation Forest for anomaly detection using scikit-learn. Following this, the authors explain the essentials of machine 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 (via LSTM), temporal convolutional networks, and transformers, with the latter three architectures applied to time-series anomaly detection. This edition has a new chapter on GANs (Generative Adversarial Networks), as well as new material covering transformer architecture in the context of time-series anomaly detection. After completing this book, you will have a thorough understanding of anomaly detection as well as an assortment of methods to approach it in various contexts, including time-series data. Additionally, you will have gained an introduction to scikit-learn, GANs, transformers, Keras, and PyTorch, empowering you to create your own machine learning- or deep learning-based anomaly detectors. What You Will Learn Understand what anomaly detection is, why it it is important, and how it is applied Grasp the core concepts of machine learning. Master traditional machine learning approaches to anomaly detection using scikit-kearn. Understand deep learning in Python using Keras and PyTorch Process data through pandas and evaluate your model's performance using metrics like F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is For Data scientists and machine learning engineers of all levels of experience interested in learning the basics of deep learning applications in anomaly detection. 58,84 €
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Technische Daten
Erscheinungsdatum
02.01.2024
Sprache
Englisch
EAN
9798868800078
Herausgeber
APRESS
Sonderedition
Nein
Autor
Suman Kalyan Adari, Sridhar Alla
Seitenanzahl
529
Auflage
2
Einbandart
Broschiert
Buch Untertitel
Implement Anomaly Detection Applications with Keras and PyTorch
Schlagwörter
Anamoly Detection, Deep Learning, Python, Keras, PyTorch, Novelty detection, Auto Encoders, Fraud Detection, Semi-supervised, Unsupervised
Thema-Inhalt
UYQ - Künstliche Intelligenz
UYQM - Maschinelles Lernen
UMX - Programmier- und Skriptsprachen, allgemein
ULJ - Open-Source und sonstige Betriebssysteme
Höhe
254 mm
Breite
17.8 cm
Hersteller: Apress, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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