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Can I read Beginning anomaly detection using Python-based deep learning : implement anomaly detection applications with Keras and PyTorch on EtoBox?

Beginning anomaly detection using Python-based deep learning : implement anomaly detection applications with Keras and PyTorch by Suman Kalyan Adari , Sridhar Alla is a nonfiction available to read on EtoBox.

What is Beginning anomaly detection using Python-based deep learning : implement anomaly detection applications with Keras and PyTorch about?

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 L

Who reads Beginning anomaly detection using Python-based deep learning : implement anomaly detection applications with Keras and PyTorch?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Suman Kalyan Adari , Sridhar Alla
Publisher
Apress L. P.
Published
2024
Language
EN
ISBN
9798868800078
Category
nonfiction
Subjects
Science, Computer Science, Programming

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