Machine Learning and Swift: Building Intelligent Apps for iOS/macOS

The book "Machine Learning and Swift" is a practical guide for iOS and macOS developers who want to integrate artificial intelligence into their applications. The author, Alexey Vorontsov, an experienced iOS developer and Data Science specialist, will take you step by step from the basics of machine learning to creating full-fledged ML features for the App Store.

What this book is about

You will learn how to use Apple's machine learning frameworks: Core ML, Create ML, Vision, Natural Language, and Sound Analysis. The book covers the complete ML workflow in Swift:

• Machine learning basics: linear regression, classification, neural networks — with examples in Swift
• Creating and training your own models with Create ML (without Python)
• Integrating ready-made Core ML models: loading, converting from TensorFlow/PyTorch, optimization
• Computer vision: object, face, and text recognition with Vision Framework
• Natural language processing: sentiment analysis, speech recognition, chatbots with Natural Language
• Sound and audio: sound classification, speech detection with Sound Analysis
• Working with data: dataset preparation, augmentation, working with Core Data and MLDataTable
• On-device ML: training directly on the device (online learning), updating models without app re-release
• Performance: model compression, using the Neural Engine, working with Metal Performance Shaders

Who this book is for

The book is intended for Swift developers with basic experience in building iOS/macOS applications. No knowledge of machine learning is required — all concepts are explained from scratch. The book will also be useful for data scientists who want to transfer their models to the Apple platform.

What you will get

• Ready-made projects: an app for emotion recognition from photos, a review sentiment analyzer, smart image search
• Clear instructions for integrating ML into SwiftUI and UIKit
• Tips for optimizing performance on older devices
• Real-world examples: recommendation systems, content filtering, predictive analytics

By the end of the book, you will be able to independently add features to your apps that once seemed like magic: object recognition in photos, text analysis, voice control, and personalized recommendations — all without sending data to a server.

This book is not just theory, but a practical tool for those who want to make their apps smarter, faster, and more modern.

Format: PDF, EPUB
Language: Russian
Level: Beginner-Intermediate (Swift)