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Introduction to deep learning for en...

Arif, Tariq M.,

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Introduction to deep learning for engineers = using python and google cloud platform /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to deep learning for engineers/ Tariq M. Arif.
Reminder of title:	using python and google cloud platform /
remainder title:	Using python and google cloud platform
Author:	Arif, Tariq M.,
Description:	1 online resource (111 p.)
Subject:	Engineering - Data processing. -
Online resource:	https://portal.igpublish.com/iglibrary/search/MCPB0006569.html
ISBN:	9781681739137

Introduction to deep learning for engineers = using python and google cloud platform /
Arif, Tariq M.,

Introduction to deep learning for engineersusing python and google cloud platform /[electronic resource] :Using python and google cloud platformTariq M. Arif. - 1 online resource (111 p.) - Synthesis lectures on mechanical engineering ;28. - Synthesis lectures on mechanical engineering ;28..

Includes bibliographical references (pages 87-92).

Access restricted to authorized users and institutions.

This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model. In recent years, deep learning-based modeling approaches have been used in a wide variety of engineering domains, such as autonomous cars, intelligent robotics, computer vision, natural language processing, and bioinformatics. Also, numerous real-world engineering applications utilize an existing pre-trained deep learning model that has already been developed and optimized for a related task. However, incorporating a deep learning model in a research project is quite challenging, especially for someone who doesn't have related machine learning and cloud computing knowledge. Keeping that in mind, this book is intended to be a short introduction of deep learning basics through the example of a practical implementation case. The audience of this short book is undergraduate engineering students who wish to explore deep learning models in their class project or senior design project without having a full journey through the machine learning theories. The case study part at the end also provides a cost-effective and step-by-step approach that can be replicated by others easily.

Mode of access: World Wide Web.

ISBN: 9781681739137Subjects--Topical Terms:

570384
Engineering
--Data processing.Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA76.5

Dewey Class. No.: 004

Introduction to deep learning for engineers = using python and google cloud platform /
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