Beginning Anomaly Detection Using Python-Based Deep Learning : Implement Anomaly Detection Applications with Keras and PyTorch

Beginning Anomaly Detection Using Python-Based Deep Learning Implement Anomaly Detection Applications with Keras and PyTorch

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...

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Detalles Bibliográficos
Otros Autores: Adari, Suman Kalyan, author (author), Alla, Sridhar, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2024.
Edición:2nd ed. 2024.
Materias:
Artificial intelligence.
Machine learning.
Python (Computer program language).
Open source software.
Artificial Intelligence.
Machine Learning.
Python.
Open Source.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009790330406719
Tabla de Contenidos:
  • Chapter 1: Introduction to Anomaly Detection
  • Chapter 2: Introduction to Data Science
  • Chapter 3: Introduction to Machine Learning
  • Chapter 4: Traditional Machine Learning Algorithms. -Chapter 5: Introduction to Deep Learning
  • Chapter 6: Autoencoders
  • Chapter 7: Generative Adversarial Networks
  • Chapter 8 Long Short-Term Memory Models
  • Chapter 9: Temporal Convolutional Networks
  • Chapter 10: Transformers
  • Chapter 11: Practical Use Cases and Future Trends of Anomaly Detection.

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