Deep Learning: Fundamentals, Theory and Applications

• Corporate Author: SpringerLink (Online service)
• Other Authors: Huang, Kaizhu (Editor, http://id.loc.gov/vocabulary/relators/edt), Hussain, Amir (Editor, http://id.loc.gov/vocabulary/relators/edt), Wang, Qiu-Feng (Editor, http://id.loc.gov/vocabulary/relators/edt), Zhang, Rui (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Cognitive Computation Trends, 2
• Subjects: Medicine.; Artificial intelligence.; Algorithms.; Biomedicine, general.; Artificial Intelligence.

The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how ma...

Table of Contents:

• Preface
• Introduction to Deep Density Models with Latent Variables
• Deep RNN Architecture: Design and Evaluation
• Deep Learning Based Handwritten Chinese Character and Text Recognition
• Deep Learning and Its Applications to Natural Language Processing
• Deep Learning for Natural Language Processing
• Oceanic Data Analysis with Deep Learning Models
• Index.