Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease
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.
iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.
Chapter 1 Getting started with Machine Learning
Chapter 2 Decision Tree Learning
Chapter 3 K-Neares Neighbor Classifier
Chapter 4 Clustering
Chapter 5 Rule learning
Chapter 6 Linear Regression and Gradient Descent
Chapter 7 Logistic Regression
Chapter 8 Neural Networks
Chapter 9 Convolutional Neural Networks and Computer Vision
Chapter 10 Word Embeddings and Natural Language Processing
Chapter 11 Machine Learning Libraries
Chapter 12 Optimizing neural networks for mobile devices
Chapter 13 Best Practices
