Book Image

Machine Learning with Swift

By : Jojo Moolayil, Alexander Sosnovshchenko, Oleksandr Baiev
Book Image

Machine Learning with Swift

By: Jojo Moolayil, Alexander Sosnovshchenko, Oleksandr Baiev

Overview of this book

Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves.
Table of Contents (18 chapters)
Title Page
Packt Upsell

Textual corpuses

For our NLP experiments, we need some reasonably big texts. I used the complete works of classical writers and statesmen from the Gutenberg project because they are in the public domain, but you can find your own texts and train models on them. If you want to use the same texts as I did, I included them in the supplementary material for this chapter under the Corpuses folder. There should be five of them: Benjamin Franklin, John Galsworthy, Mark Twain, William Shakespeare, and Winston Churchill. Create a new Jupyter notebook and load Mark Twain's corpus as one long string:

import zipfile 
zip_ref = zipfile.ZipFile('', 'r') 
In [1]: 
import codecs 
In [2]: 
one_long_string = "" 
with'Corpuses/MarkTwain.txt', 'r', 'utf-8-sig') as text_file: 
    one_long_string = 
In [3]: 
u"size, very elegantly wrought and dressed in the fancifulrncostumes of two centuries...