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Machine Learning with Swift : Artificial Intelligence for iOS - Alexander Sosnovshchenko

Machine Learning with Swift

Artificial Intelligence for iOS

By: Alexander Sosnovshchenko

eText | 28 February 2018 | Edition Number 1

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Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease

About This Book

  • Implement effective machine learning solutions for your iOS applications
  • Use Swift and Core ML to build and deploy popular machine learning models
  • Develop neural networks for natural language processing and computer vision

Who This Book Is For

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.

What You Will Learn

  • Learn rapid model prototyping with Python and Swift
  • Deploy pre-trained models to iOS using Core ML
  • Find hidden patterns in the data using unsupervised learning
  • Get a deeper understanding of the clustering techniques
  • Learn modern compact architectures of neural networks for iOS devices
  • Train neural networks for image processing and natural language processing

In Detail

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.

Style and approach

A comprehensive guide that teaches how to implement machine learning apps for iOS from scratc

on
Desktop
Tablet
Mobile

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