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

KNN pros

  • It's simple to implement if you are not going for optimized versions which use advanced data structures.
  • It's easy to understand and interpret. The algorithm is well studied theoretically, and much known about its mathematical properties in different settings.
  • You can plug in any distance metric. This allows working with complex objects, like time series, graphs, geographical coordinates, and basically anything you can define distance metric for.
  • Algorithms can be used for classification, ranking, regression (using neighbors average or weighted average), recommendations, and can even provide (a kind of) probabilistic output—what proportion of neighbors voted for this class.
  • It's easy to incorporate new data in the model or remove outdated data from it. This makes KNN a good choice for online learning (see Chapter 1Getting Started with Machine Learning) systems.