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You're reading from Mobile Artificial Intelligence Projects Develop seven projects on your smartphone using artificial intelligence and deep learning techniques

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789344073

Length 312 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow Lite

Concepts

Artificial Intelligence

Authors (3):

Arun Padmanabhan

Karthikeyan NG

Matt Cole

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Table of Contents (12) Chapters

Preface

1. Artificial Intelligence Concepts and Fundamentals

2. Creating a Real-Estate Price Prediction Mobile App FREE CHAPTER

3. Implementing Deep Net Architectures to Recognize Handwritten Digits

4. Building a Machine Vision Mobile App to Classify Flower Species

5. Building an ML Model to Predict Car Damage Using TensorFlow

6. PyTorch Experiments on NLP and RNN

7. TensorFlow on Mobile with Speech-to-Text with the WaveNet Model

8. Implementing GANs to Recognize Handwritten Digits

9. Sentiment Analysis over Text Using LinearSVC

10. What is Next?

11. Other Books You May Enjoy

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Building the ML model using scikit–learn

In this section, we will build our own model. There are existing datasets available that are related to Twitter feed data on the topic of product and movie reviews. You can pick a dataset that suits you; in this chapter, we will pick a dataset that has customer reviews.

A dataset that contains both positive and negative reviews of customers can be found at http://boston.lti.cs.cmu.edu/classes/95-865-K/HW/HW3/. You can download the dataset from the following link: http://boston.lti.cs.cmu.edu/classes/95-865-K/HW/HW3/epinions3.zip.

The aforementioned dataset has both positive and negative feedback about a product, as shown in the following screenshot:

We will train the dataset using the scikit-learn pipeline and LinearSVC. Let's take a closer look at both of these.

...

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Authors (3)

Karthikeyan NG is the Head of Engineering and Technology at the Indian lifestyle and 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.

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Padmanabhan

Arun Padmanabhan is a Machine Learning consultant with over 8 years of experience building end-to-end machine learning solutions and applications. Currently working with a couple of start-ups in the Financial and Insurance industries, he specializes in automating manual workflows using AI and creating Machine Vision and NLP applications. In past, he has led the data science team of a Singapore based product startup in the restaurant domain. He also has built stand-alone and integrated Machine Learning solutions in the Manufacturing, Shipping and e-commerce domains over the years. His interests are in research, development and applications of Artificial Intelligence and Deep Architectures.

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Matt Cole

Matt R. Cole is a developer and author with 30 years' experience. Matt is the owner of Evolved AI Solutions, a provider of advanced Machine Learning/Bio-AI, Microservice and Swarm technologies. Matt is recognized as a leader in Microservice and Artificial Intelligence development and design. As an early pioneer of VOIP, Matt developed the VOIP system for NASA for the International Space Station and Space Shuttle. Matt also developed the first Bio Artificial Intelligence framework which completely integrates mirror and canonical neurons. In his spare time Matt authors books, and continues his education taking every available course in advanced mathematics, AI/ML/DL, Quantum Mechanics/Physics, String Theory and Computational Neuroscience.

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