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...

Full description

Saved in:
Bibliographic Details
Main Author Liu, Yuxi (Hayden)
Other Authors Mehta, Saransh
Format Electronic eBook
LanguageEnglish
Published Birmingham : Packt Publishing, Limited, 2019.
Subjects
Python (Computer program language)
Machine learning.
Neural networks (Computer science)
elektronické knihy
electronic books
Online AccessFull text
ISBN1788990501
9781788990509
9781788998086
1788998081
Physical Description1 online resource (303 pages)

Cover

Table of Contents:
  • 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.

Similar Items