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

Finding frequent item sets

The first step of the algorithm that we implement is based on the support measure. This function returns a set of all item sets with support larger than minSupport:

func frequentItemSets(minSupport: Double) -> Set<ItemSet> { 
    var itemSets = Set<ItemSet>() 
    let emptyItemSet: ItemSet = ItemSet() 
    supporters[emptyItemSet] = Array(0 ..< transactions.count) 

Here we use the priority queue data structure to keep track of possible extensions.


There is no priority queue implementation in the Foundation or Swift standard libraries, and standard data structures are out of the scope of this book. We are using the open source implementation by David Kopec (MIT license):

To make it work with item sets we had to change the code a bit—instead of being parameterized with the comparable types, it is now parameterized with types conforming to the equatable protocol:

    var queue = PriorityQueue...