Book Image

Mobile Artificial Intelligence Projects

By : Karthikeyan NG, Arun Padmanabhan, Matt R. Cole
Book Image

Mobile Artificial Intelligence Projects

By: Karthikeyan NG, Arun Padmanabhan, Matt R. Cole

Overview of this book

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 (12 chapters)
PyTorch Experiments on NLP and RNN
TensorFlow on Mobile with Speech-to-Text with the WaveNet Model
Implementing GANs to Recognize Handwritten Digits

Building an ML Model to Predict Car Damage Using TensorFlow

In this chapter, we will build a system that detects the level of damage that's been done to a vehicle by analyzing photographs using transfer learning. A solution like this will be helpful in reducing the cost of insurance claims, as well as making the process simpler for vehicle owners. If the system is implemented properly, in an ideal scenario, the user will upload a bunch of photographs of the damaged vehicle, the photos will go through damage assessment, and the insurance claim will be processed automatically.

There are a lot of risks and challenges involved in implementing a perfect solution for this use case. To start with, there are multiple unknown conditions that could have caused damage to the car. We are not aware of the outdoor environment, surrounding objects, light in the area, and the quality of...