Mobile Artificial Intelligence Projects

Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch

Mobile Artificial Intelligence Projects

Karthikeyan NG, Arun Padmanabhan, Matt R. Cole
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Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch
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Book Details

ISBN 139781789344073
Paperback312 pages

Book Description

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

This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn 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 PyTorch across Android and iOS platforms.

By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users.

Table of Contents

Chapter 4: Building a Machine Vision Mobile App to Classify Flower Species
Chapter 5: Building an ML Model to Predict Car Damage Using TensorFlow
Chapter 6: PyTorch Experiments on NLP and RNN
Chapter 7: TensorFlow on Mobile with Speech-to-Text with the WaveNet Model
Chapter 8: Implementing GANs to Recognize Handwritten Digits

What You Will Learn

  • Explore the concepts and fundamentals of AI, deep learning, and neural networks
  • Implement use cases for machine vision and natural language processing
  • Build an ML model to predict car damage using TensorFlow
  • Deploy TensorFlow on mobile to convert speech to text
  • Implement GAN to recognize hand-written digits
  • Develop end-to-end mobile applications that use AI principles
  • Work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch

Authors

Table of Contents

Chapter 4: Building a Machine Vision Mobile App to Classify Flower Species
Chapter 5: Building an ML Model to Predict Car Damage Using TensorFlow
Chapter 6: PyTorch Experiments on NLP and RNN
Chapter 7: TensorFlow on Mobile with Speech-to-Text with the WaveNet Model
Chapter 8: Implementing GANs to Recognize Handwritten Digits

Book Details

ISBN 139781789344073
Paperback312 pages
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