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

Understanding the regression task

Recall that the regression task is of a particular case of supervised learning, where real numbers take the place of labels. It is the primary difference from the classification, where all labels are categories. You can use regression analysis to study the interactions between two or more variables; for example, the way personal computer price depends on the computer's characteristics, such as a number of CPU cores and the type, memory size, video card characteristics, and storage type and size. In the context of regression, we usually call features independent variables and labels dependent variables. In our example, independent variables are the computer's characteristics and the dependent variable is its price. Having a regression model, we can predict which machine is better to buy. Moreover, regression allows you to make educated guesses about the contribution of each feature to the final price. Could be an idea for the next viral app.

Regression analysis...