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Mobile Artificial Intelligence Projects

You're reading from  Mobile Artificial Intelligence Projects

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Pages 312 pages
Edition 1st Edition
Languages
Authors (3):
Karthikeyan NG Karthikeyan NG
Profile icon Karthikeyan NG
Arun Padmanabhan Arun Padmanabhan
Profile icon Arun Padmanabhan
Matt Cole Matt Cole
Profile icon Matt Cole
View More author details

Table of Contents (12) Chapters

Preface 1. Artificial Intelligence Concepts and Fundamentals 2. Creating a Real-Estate Price Prediction Mobile App 3. Implementing Deep Net Architectures to Recognize Handwritten Digits 4. Building a Machine Vision Mobile App to Classify Flower Species 5. Building an 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 is Next? 11. Other Books You May Enjoy

Summary

At this point, you should be able to build your own TensorFlow model and convert it into a Core ML model so that it can be used in an iOS application. The same TensorFlow model can be converted into a TensorFlow Lite model, which can then be used in an Android application or iOS application. Now, you can take on this task and experiment with the results. That said, we are now ready to move on to the next chapter.

In the next chapter, you will use the knowledge we have acquired in this book to move on and explore how you can build your own application.

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