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

Introduction to Computer Vision

Computer Vision can be defined as the subset of AI where we can teach a computer to see. We cannot just add a camera to a machine in order for it to see. For a machine to actually view the world like people or animals do, it relies on Computer Vision and image recognition techniques. Reading barcodes and face recognition are examples of Computer Vision. Computer Vision can be described as that part of the human brain that processes the information that's perceived by the eyes, nothing else.

Image recognition is one of the interesting uses of Computer Vision from an AI standpoint. The input that is received through Computer Vision on the machine is interpreted by the image recognition system, and based on what it sees, the output is classified.

In other words, we use our eyes to capture the objects around us, and those objects/images are processed...