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Machine Learning for Mobile

You're reading from   Machine Learning for Mobile Practical guide to building intelligent mobile applications powered by machine learning

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781788629355
Length 274 pages
Edition 1st Edition
Tools
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Authors (2):
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Avinash Venkateswarlu Avinash Venkateswarlu
Author Profile Icon Avinash Venkateswarlu
Avinash Venkateswarlu
Revathi Gopalakrishnan Revathi Gopalakrishnan
Author Profile Icon Revathi Gopalakrishnan
Revathi Gopalakrishnan
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Machine Learning on Mobile FREE CHAPTER 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 12. Question and Answers 13. Other Books You May Enjoy

Introduction to unsupervised learning algorithms

Consider a scenario where a child is given a bag full of beads of different sizes, colors, shapes, and made of various materials. We just leave to the child do whatever they want with the whole bag of beads. 

There are various things the child could do, based on their interests:

  • Separate the beads into categories based on size
  • Separate the beads into categories based on shape
  • Separate the beads into categories based on a combination of color and shape
  • Separate the beads into categories based on a combination of material, color, and shape

The possibilities are endless. However, the child without any prior teaching is able to go through the beads and uncover patterns of which it doesn't need any any prior knowledge at all. They are discovering the patterns purely on the basis of going through the beads at hand,...

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