Mobile Artificial Intelligence Projects: Develop seven projects on your smartphone using artificial intelligence and deep learning techniques - Softcover

NG, Karthikeyan; Padmanabhan, Arun; R. Cole, Matt

Softcover

ISBN 10: 1789344077 ISBN 13: 9781789344073

Publisher: Packt Publishing, 2019

Synopsis

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

Key Features

• Build practical, real-world AI projects on Android and iOS
• Implement tasks such as recognizing handwritten digits, sentiment analysis, and more
• Explore the core functions of machine learning, deep learning, and mobile vision

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.

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

Who this book is for

Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.

Table of Contents

1. Artificial Intelligence Concepts and Fundamentals
2. Creating a Real-Estate price prediction mobile app
3. Implementing Deepnet Architectures to Recognize Hand Written Digits
4. Building a Machine Vision Mobile App to Classify Flower Species
5. Building a 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's next?

About this title

About the Author

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.

Edition details

• Publisher: Packt Publishing
• Publication date: 2019
• Language: English
• ISBN 10: 1789344077
• ISBN 13: 9781789344073
• Binding: Paperback
• Number of pages: 312