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Neural Networks and Deep Learning A Textbook /

This book covers both classical and modern models in deep learning. The chapters of this book span three categories: 1. The basics of neural networks: The backpropagation algorithm is discussed in Chapter 2. Many traditional machine learning models can be understood as special cases of neural networ...

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Detalles Bibliográficos
Autor principal: Aggarwal, Charu C. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Lenguaje:inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edición:2nd ed. 2023.
Materias:
Machine learning.
Data mining.
Artificial intelligence.
Expert systems (Computer science).
Natural language processing (Computer science).
Machine Learning.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Knowledge Based Systems.
Natural Language Processing (NLP).
Acceso en línea:https://doi.org/10.1007/978-3-031-29642-0
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Tabla de Contenidos:
  • An Introduction to Neural Networks
  • The Backpropagation Algorithm
  • Machine Learning with Shallow Neural Networks
  • Deep Learning: Principles and Training Algorithms
  • Teaching a Deep Neural Network to Generalize
  • Radial Basis Function Networks
  • Restricted Boltzmann Machines
  • Recurrent Neural Networks
  • Convolutional Neural Networks
  • Graph Neural Networks
  • Deep Reinforcement Learning
  • Advanced Topics in Deep Learning.

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