Hands-On Deep Learning Architectures with Python : Create Deep Neural Networks to Solve Computational Problems Using TensorFlow and Keras.

This book explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations to help you understand the concepts and ideas required to build efficient artificial intelligence systems, this book will help you construct deep models using popular f...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Liu, Yuxi (Hayden)
Otros Autores: Mehta, Saransh
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited, 2019.
Temas:
Python (Computer program language)
Machine learning.
Neural networks (Computer science)
Neural Networks, Computer
Machine Learning
Python (Langage de programmation)
Apprentissage automatique.
Réseaux neuronaux (Informatique)
Natural language & machine translation.
Neural networks & fuzzy systems.
Artificial intelligence.
COMPUTER SCIENCE > General.
Machine learning
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Hands-on deep learning architectures with python: create deep neural networks to solve computational problems using TensorFlow and Keras
  • Contributors
  • Table of Contents
  • Preface
  • Section 1: The Elements of Deep Learning
  • Chapter 1: Getting Started with Deep Learning
  • Chapter 2: Deep Feedforward Networks
  • Chapter 3: Restricted Boltzmann Machines and Autoencoders
  • Section 2: Convolutional Neural Networks
  • Chapter 4: CNN Architecture
  • Chapter 5: Mobile Neural Networks and CNNs
  • Section 3: Sequence Modeling
  • Chapter 6: Recurrent Neural Networks
  • Section 4: Generative Adversarial Networks (GANs)
  • Chapter 7: Generative Adversarial Networks
  • Section 5: The Future of Deep Learning and Advanced Artificial Intelligence
  • Chapter 8: New Trends of Deep Learning
  • Other Books You May Enjoy
  • Index.

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