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Introduction to Deep Learning for Engineers

SYNTHESIS LECT MECH ENG: INTRO DEEP LEARNING ENGINEERS

Information Technology

Computing & Information Technology

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B2B GT

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B2B & B2C

<P>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.</P>

Introduction to Deep Learning for Engineers: Using Python and Google Cloud Platform

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Synthesis Lectures on Mechanical Engineering.
Copyright Page.
Title Page.
Other Frontmatter.
Table of Contents.
Preface.
Acknowledgments.
1: Introduction: Python and Array Operations.
2: Introduction to PyTorch.
3: Basic Artificial Neural Network and Architectures.
4: Introduction to Deep Learning.
5: Deep Transfer Learning.
6: Setting Up PyTorch and Google Cloud Platform Console.
7: Case Study: Practical Implementation Through Transfer Learning.
Bibliography.
Author&#x2019;s Biography.

Introduction to Deep Learning for Engineers: Using Python and Google Cloud Platform.css-1p8rvzy{position:absolute;padding-left:8px;}

Introduction to Deep Learning for Engineers: Using Python and Google Cloud Platform