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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

Common NLP approaches and subtasks

Most programmers are familiar with the simplest way of processing natural language: regular expressions. There are many regular expression implementations for different programming languages ​​that differ in small details. Because of these details, the same regular expression on various platforms can produce different results or not work at all. The two most popular standards are POSIX and Perl. The Foundation framework, however, contains its own version of regular expressions, based on the ICU C++ library. It is an extension of the POSIX standard for Unicode strings.

Why are we even talking about regular expressions here? Regular expressions are a great example of what NLP specialists call heuristics—manually written rules, ad hoc solutions, and describing a complex structure in such a way that all exceptions and variations...

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