Beginning Anomaly Detection Using Python-Based Deep Learning With Keras and PyTorch /

• Main Authors: Alla, Sridhar (Author, http://id.loc.gov/vocabulary/relators/aut), Adari, Suman Kalyan (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
• Edition: 1st ed. 2019.
• Subjects: Artificial intelligence.; Python (Computer program language).; Open source software.; Computer programming.; Artificial Intelligence.; Python.; Open Source.

Utilize this easy-to-follow 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 semi-supervised and unsupervised anomaly detection tasks. This...

Table of Contents:

• Chapter 1: What is Anomaly Detection?
• Chapter 2: Traditional Methods of Anomaly Detection
• Chapter 3: Introduction to Deep Learning
• Chapter 4: Autoencoders
• Chapter 5: Boltzmann Machines
• Chapter 6: Long Short-Term Memory Models
• Chapter 7: Temporal Convolutional Network
• Chapter 8: Practical Use Cases of Anomaly Detection
• Appendix A: Introduction to Keras
• Appendix B: Introduction to PyTorch.