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

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

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...

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Detalles Bibliográficos
Autores principales: Alla, Sridhar. author (author), Adari, Suman Kalyan. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2019.
Edición:1st ed. 2019.
Materias:
Artificial intelligence.
Python (Computer program language).
Open source software.
Artificial Intelligence.
Python.
Open Source.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630916706719
Tabla de Contenidos:
  • 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.

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