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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Mobile Artificial Intelligence
Projects
Develop seven projects on your smartphone using artificial
intelligence and deep learning techniques
Karthikeyan NG
Arun Padmanabhan
Matt R. Cole
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Mobile Artificial Intelligence Projects
Copyright © 2019 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form
or by any means, without the prior written permission of the publisher, except in the case of brief quotations
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have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products
mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy
of this information.
Commissioning Editor: Pravin Dhandre
Acquisition Editor: Yogesh Deokar
Content Development Editor: Snehal Kolte
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Copy Editor: Safis Editing
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First published: March 2019
Production reference: 1300319
Published by Packt Publishing Ltd.
Livery Place
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r sth ISBN 978-1-78934-407-3
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
To my wife, Nanthana, for putting up with me during the course of this book. I know it must not
have been easy.
To my parents, for their constant support.
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Contributors
About the authors
Karthikeyan NG is the Head of Engineering and Technology at the Indian lifestyle &
fashion retail brand. He served as a software engineer at Symantec Corporation and has
worked with 2 US-based startups as an early employee and has built various products. He
has 9+ years of experience in various scalable products using Web, Mobile, ML, AR, and VR
technologies. He is an aspiring entrepreneur and technology evangelist. His interests lie in
exploring new technologies and innovative ideas to resolve a problem. He has also bagged
prizes from more than 15 hackathons, is a TEDx speaker and a speaker at technology
conferences and meetups as well as guest lecturer at a Bengaluru University. When not at
work, he is found trekking.
I would like to extend my gratitude to Manthan Patel for presenting the idea of the book,
and to Snehal Kolte for her tenacity. Thanks to Naveen, the technical editor, and the entire
editorial team. I would also like to thank the open source community for making this book
possible with the frameworks on both Android and iOS platforms.
Arun Padmanabhan is a machine learning consultant with over 8 years of experience
building end-to-end machine learning solutions and applications. Presently working with a
couple of start-ups in the financial and insurance sectors, he specializes in automating
manual workflows using AI and creating machine vision and NLP applications. Previously,
he led the data science team of a Singapore-based product start-up in the restaurant
domain. Over the years, he has also built standalone and integrated machine learning
.de solutions in the manufacturing, shipping, and e-commerce domains. His interests lie in
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tkca Intelligence framework which completely integrates mirror and canonical neurons. He
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
About the reviewers
Subhash Shah works as head of technology at AIMDek Technologies Pvt. Ltd. He is an
experienced solutions architect with over 12 years of experience. He holds a degree in
information technology. He is an advocate of open source development and its utilization
in solving critical business problems at a reduced cost. His interests include microservices,
data analysis, machine learning, AI, and databases. He is an admirer of quality code and
test-driven development (TDD). His technical skills include, but are by no means limited
to, translating business requirements into scalable architecture, designing sustainable
solutions, and project delivery. He is a coauthor of MySQL 8 Administrator's Guide and
Hands-On High Performance with Spring 5.
Rajib Bhattacharya currently works as a pre-sales consultant with a premier IT solution
provider in the Middle East. Rajib has more than 14 years of experience in IT consulting,
defining solution architecture, and pre-sales. He is a seasoned architect focusing on
analytics, data warehousing, big data, and cognitive computing. He holds multiple patents
and is also an author of two books in the field of analytics. He is passionate about helping
clients to consolidate their enterprise data, thereby enabling them to make valuable
business decisions. Rajib holds a MCA degree from West Bengal University of Technology.
He has developed and delivered various training programs on analytics and cognitive
computing.
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Table of Contents
Preface 1
Chapter 1: Artificial Intelligence Concepts and Fundamentals 6
AI versus machine learning versus deep learning 7
Evolution of AI 8
The mechanics behind ANNs 11
Biological neurons 12
Working of artificial neurons 13
Scenario 1 16
Scenario 2 17
Scenario 3 19
ANNs 21
Activation functions 23
Sigmoid function 25
Tanh function 26
ReLU function 27
Cost functions 29
Mean squared error 29
Cross entropy 30
Gradient descent 31
Backpropagation – a method for neural networks to learn 33
Softmax 34
TensorFlow Playground 37
Summary 41
Further reading 42
Chapter 2: Creating a Real-Estate Price Prediction Mobile App 43
Setting up the artificial intelligence environment 44
Downloading and installing Anaconda 44
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r sth Installing dependencies 47
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.de Serving the model as an API 58
timiL Building a simple API to add two numbers 58
,gn Building an API to predict the real estate price using the saved model 60
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Table of Contents
Adding a functionality to consume the RESTful API that serves the model 76
Additional notes 81
Creating an iOS app to predict house prices 81
Downloading and installing Xcode 81
Creating a new iOS project with a single screen 82
Designing the layout of the screen 84
Adding a functionality to accept input 89
Adding a functionality to consume the RESTful API that serves the model 89
Additional notes 90
Summary 90
Chapter 3: Implementing Deep Net Architectures to Recognize
Handwritten Digits 91
Building a feedforward neural network to recognize handwritten
digits, version one 92
Building a feedforward neural network to recognize handwritten
digits, version two 97
Building a deeper neural network 99
Introduction to Computer Vision 101
Machine learning for Computer Vision 102
Conferences help on Computer Vision 102
Summary 103
Further reading 103
Chapter 4: Building a Machine Vision Mobile App to Classify Flower
Species 104
CoreML versus TensorFlow Lite 105
CoreML 105
TensorFlow Lite 105
What is MobileNet? 105
Datasets for image classification 106
Creating your own image dataset using Google images 108
Alternate approach of creating custom datasets from videos 115
.d Building your model using TensorFlow 116
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timiL Transfer learning basics 126
,gn Approaches to transfer learning 127
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uP Installing TensorFlow 128
tkca Training the images 129
P .9 Building our own model 130
10 Retraining with our own images 130
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NG, Karthikeyan, et al. Mobile Artificial Intelligence Projects : Develop Seven Projects on Your Smartphone Using Artificial Intelligence and Deep Learning
Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
Table of Contents
Architecture 131
Distortions 133
Hyperparameters 133
Image dataset collection 134
Introduction to Beautiful Soup 134
Examples 139
Dataset preparation 141
Running the training script 150
Setting up a web application 150
Summary 159
Chapter 6: PyTorch Experiments on NLP and RNN 160
PyTorch 160
The features of PyTorch 160
Installing PyTorch 161
PyTorch basics 163
Using variables in PyTorch 165
Plotting values on a graph 167
Building our own model network 170
Linear regression 170
Classification 173
Simple neural networks with torch 178
Saving and reloading data on the network 180
Running with batches 182
Optimization algorithms 183
Recurrent neural networks 187
The MNIST database 187
RNN classification 187
RNN cyclic neural network – regression 191
Natural language processing 196
Affine maps 197
Non-linearities 197
Objective functions 198
Building network components in PyTorch 199
BoW classifier using logistic regression 199
.de Summary 204
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.de Architecture 208
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,gn The algorithm's components 211
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Techniques, Packt Publishing, Limited, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/nyulibrary-ebooks/detail.action?docID=5744466.
Created from nyulibrary-ebooks on 2022-10-26 11:50:53.
