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Challenges And Opportunities For Deep Learning Applications In Industry 40 Vaishali Mehta

  • SKU: BELL-47250380
Challenges And Opportunities For Deep Learning Applications In Industry 40 Vaishali Mehta
$ 31.00 $ 45.00 (-31%)

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Challenges And Opportunities For Deep Learning Applications In Industry 40 Vaishali Mehta instant download after payment.

Publisher: Bentham Science Publishers
File Extension: PDF
File size: 14.15 MB
Pages: 228
Author: Vaishali Mehta, Dolly Sharma, Monika Mangla, Anita Gehlot, Rajesh Singh, Sergio Márquez Sánchez
ISBN: 9789815036077, 9815036076
Language: English
Year: 2022

Product desciption

Challenges And Opportunities For Deep Learning Applications In Industry 40 Vaishali Mehta by Vaishali Mehta, Dolly Sharma, Monika Mangla, Anita Gehlot, Rajesh Singh, Sergio Márquez Sánchez 9789815036077, 9815036076 instant download after payment.

The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement despite several issues. One of the limitations for technical progress is the bottleneck encountered due to the enormous increase in data volume for processing, comprising various formats, semantics, qualities and features. Deep learning enables detection of meaningful features that are difficult to perform using traditional methods.

The book takes the reader on a technological voyage of the industry 4.0 space. Chapters highlight recent applications of deep learning and the associated challenges and opportunities it presents for automating industrial processes and smart applications.

Chapters introduce the reader to a broad range of topics in deep learning and machine learning. Several deep learning techniques used by industrial professionals are covered, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical project methodology. Readers will find information on the value of deep learning in applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.

The book also discusses prospective research directions that focus on the theory and practical applications of deep learning in industrial automation. Therefore, the book aims to serve as a comprehensive reference guide for industrial consultants interested in industry 4.0, and as a handbook for beginners in data science and advanced computer science courses.

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