Book Image

Intelligent Mobile Projects with TensorFlow

By : Jeff Tang
Book Image

Intelligent Mobile Projects with TensorFlow

By: Jeff Tang

Overview of this book

As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips.
Table of Contents (14 chapters)

Generating and Enhancing Images with GAN

Since deep learning took off in 2012, some people think no new idea has been more interesting or promising than Generative Adversarial Network (GAN), introduced by Ian Goodfellow in 2014 in the paper, Generative Adversarial Networks (https://arxiv.org/abs/1406.2661). In fact, Yann LeCun, the Facebook AI research director and one of the pioneering deep learning researchers, referred to GAN and adversarial training as “the most interesting idea in the last 10 years in machine learning.” Because of this, how can we not cover it here, to understand why GAN is so exciting and how to build GAN models and run them on iOS and Android?

In this chapter, we'll first give an overview of what a GAN is, how it works, and why it has such great potential. Then we'll go through two GAN models: one basic GAN model that can be used...