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Machine Learning with Swift

You're reading from   Machine Learning with Swift Artificial Intelligence for iOS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787121515
Length 378 pages
Edition 1st Edition
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Authors (3):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Oleksandr Baiev Oleksandr Baiev
Author Profile Icon Oleksandr Baiev
Oleksandr Baiev
Alexander Sosnovshchenko Alexander Sosnovshchenko
Author Profile Icon Alexander Sosnovshchenko
Alexander Sosnovshchenko
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Machine Learning FREE CHAPTER 2. Classification – Decision Tree Learning 3. K-Nearest Neighbors Classifier 4. K-Means Clustering 5. Association Rule Learning 6. Linear Regression and Gradient Descent 7. Linear Classifier and Logistic Regression 8. Neural Networks 9. Convolutional Neural Networks 10. Natural Language Processing 11. Machine Learning Libraries 12. Optimizing Neural Networks for Mobile Devices 13. Best Practices

Best Practices

"The purpose of a storyteller is not to tell you how to think, but to give you questions to think upon."

– Brandon Sanderson, The Way of Kings

Imagine the field of AI as a huge national park. In previous chapters, we guided you along several exciting trails and showed you the most interesting sights for mobile developers. But there is still so much more that is unexplored. So, in this chapter, we want to provide you with a map of the common paths, from idea to production. We've outlined dangerous zones and left notes on solo hiking best practices! We also want to point out several interesting directions for your future exploration.

In this chapter, we will discuss the following topics:

  • The path from idea to production
  • Common pitfalls in machine learning projects also known as machine learning gremlins
  • Machine learning best practices...
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