In this chapter, we first described how a drawing classification model works, then covered how to train such a model using the high-level TensorFlow Estimator API. We looked at how to write Python code to make predictions with a trained model, then discussed in great detail how to find the right input and output node names and how to freeze and transform the model in the right way so mobile apps can use it. We also offered a new method to build a new TensorFlow custom iOS library, and a step-by-step tutorial on building a TensorFlow custom library for Android, to fix runtime errors when using the model. Finally, we showed the iOS and Android code that captures and shows user drawings, converts them to the data expected by the model, and processes and presents the classification results returned by the model. Hopefully, you have learned as much as you have had fun over...
Intelligent Mobile Projects with TensorFlow
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Intelligent Mobile Projects with TensorFlow
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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)
Preface
Free Chapter
Getting Started with Mobile TensorFlow
Classifying Images with Transfer Learning
Detecting Objects and Their Locations
Transforming Pictures with Amazing Art Styles
Understanding Simple Speech Commands
Describing Images in Natural Language
Recognizing Drawing with CNN and LSTM
Predicting Stock Price with RNN
Generating and Enhancing Images with GAN
Building an AlphaZero-like Mobile Game App
Using TensorFlow Lite and Core ML on Mobile
Developing TensorFlow Apps on Raspberry Pi
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