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Machine Learning for Mobile

You're reading from  Machine Learning for Mobile

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781788629355
Pages 274 pages
Edition 1st Edition
Languages
Authors (2):
Revathi Gopalakrishnan Revathi Gopalakrishnan
Profile icon Revathi Gopalakrishnan
Avinash Venkateswarlu Avinash Venkateswarlu
Profile icon Avinash Venkateswarlu
View More author details

Table of Contents (19) Chapters

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Introduction to Machine Learning on Mobile 2. Supervised and Unsupervised Learning Algorithms 3. Random Forest on iOS 4. TensorFlow Mobile in Android 5. Regression Using Core ML in iOS 6. The ML Kit SDK 7. Spam Message Detection 8. Fritz 9. Neural Networks on Mobile 10. Mobile Application Using Google Vision 11. The Future of ML on Mobile Applications 1. Question and Answers 2. Other Books You May Enjoy Index

Hand-on samples using Fritz


In this section, we will try using Fritz and the models that we've already created for iOS and Android using Core ML and TensorFlow for mobile and build iOS and Android mobile applications using Fritz. Along with this, we will see how to use the Fritz built-in models, such as object detection and image labeling.

Using the existing TensorFlow for mobile model in an Android application using Fritz

In this section, we are going to see how to use a TensorFlow for mobile model that we already have created in an Android mobile application using the Fritz toolkit. We are going to take the sample model that we created using TensorFlow for mobile to do the summation (a+b). We will go through the detailed steps required to achieve this objective.

Registering with Fritz

In order to use Fritz, you must sign up for an account at the Fritz web portal:

  1. Go to https://fritz.ai/
  2. Click on Login on the top menu 
  3. Click on Create an account
  4. Enter your details and submit
  5. Create a new project...
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