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Mobile Artificial Intelligence Projects

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

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Length 312 pages
Edition 1st Edition
Languages
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Authors (3):
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Arun Padmanabhan Arun Padmanabhan
Author Profile Icon Arun Padmanabhan
Arun Padmanabhan
Karthikeyan NG Karthikeyan NG
Author Profile Icon Karthikeyan NG
Karthikeyan NG
Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
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Table of Contents (12) Chapters Close

Preface 1. Artificial Intelligence Concepts and Fundamentals FREE CHAPTER 2. Creating a Real-Estate Price Prediction Mobile App 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

Preface

We're witnessing a revolution in Artificial Intelligence (AI), thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying AI techniques to design applications for natural language processing (NLP), robotics, and computer vision.

The book teaches you how to harness the power of AI in mobile applications, along with learning the core functions of NLP, neural networks, deep learning, and the Mobile Vision API. This book features a range of projects covering tasks such as automated reasoning, facial recognition, digital assistants, automatic text generation, and personalized news and stories. You will learn how to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries such as TensorFlow Lite, CoreML, and the Snapdragon Neural Processing Engine (NPE) across the Android and iOS platforms.

By the end of this book, you will be capable of developing exciting and intuitive mobile applications, delivering a customized and personalized experience to users.

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