Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R /

Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Lea...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Beysolow, Taweh II (Author)
Format: Electronic eBook
Language:Inglés
Published: [Berkeley, California?] : Apress, [2017]
Series:Books for professionals by professionals.
Subjects:
Machine learning.
Big data.
R (Computer program language)
Apprentissage automatique.
Données volumineuses.
R (Langage de programmation)
Artificial intelligence.
Programming & scripting languages: general.
Business mathematics & systems.
BUSINESS & ECONOMICS > Management.
BUSINESS & ECONOMICS > Reference.
BUSINESS & ECONOMICS > Skills.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • Introduction to deep learning
  • Mathematical review
  • A review of optimization and machine learning
  • Single and multilayer perceptron models
  • Convolutional neural networks (CNNs)
  • Recurrent neural networks (RNNs)
  • Autoencoders, restricted boltzmann machines, and deep belief networks
  • Experimental design and heuristics
  • Hardware and software suggestions
  • Machine learning example problems
  • Deep learning and other example problems
  • Closing statements.

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