Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing

Name: Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing
Brand: BENTHAM SCIENCE PUB
SKU: 9789815079234
Price: 1453 CZK
Availability: InStock

Autor: Rajesh Doriya

Jazyk:

Vazba: Brožovaná

Vydavatel: BENTHAM SCIENCE PUB

Dostupnost: Skladem u dodavatele

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This book is a detailed reference guide on deep learning and its applications. It aims to provide a...

Informace o knize

Autor

Rajesh Doriya

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2023

Stránek

270

EAN

9789815079234

ISBN

9815079239

Enbook ID

44185172

Vydavatel

BENTHAM SCIENCE PUB

Hmotnost

653

Rozměry

178 x 254 x 18

Kompletní popis

This book is a detailed reference guide on deep learning and its applications. It aims to provide a basic understanding of deep learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by computer science academics and researchers. By the end of the book, the reader will become familiar with different deep learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries.

This book is divided into three parts. The first part explains the basic operating understanding, history, evolution, and challenges associated with deep learning. The basic concepts of mathematics and the hardware requirements for deep learning implementation, and some of its popular frameworks for medical applications are also covered.

The second part is dedicated to sentiment analysis using deep learning and machine learning techniques. This book section covers the experimentation and application of deep learning techniques and architectures in real-world applications. It details the salient approaches, issues, and challenges in building ethically aligned machines. An approach inspired by traditional Eastern thought and wisdom is also presented.

The final part covers artificial intelligence approaches used to explain the machine learning models that enhance transparency for the benefit of users. A review and detailed description of the use of knowledge graphs in generating explanations for black-box recommender systems and a review of ethical system design and a model for sustainable education is included in this section. An additional chapter demonstrates how a semi-supervised machine learning technique can be used for cryptocurrency portfolio management.

The book is a timely reference for academicians, professionals, researchers and students at engineering and medical institutions working on artificial intelligence applications.

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