Machine Learning and Swift: iOS and macOS Development

The book "Machine Learning and Swift" is a practical guide for iOS and macOS developers who want to master artificial intelligence technologies and integrate them into their applications. The author, Alexey Voronov, a senior iOS developer with experience implementing ML solutions in production projects, will guide you step by step from the basics of machine learning to creating full-fledged intelligent applications.

What is this book about?

• Fundamental concepts of machine learning: linear regression, decision trees, neural networks, and their implementation in Swift.
• Working with the Core ML framework: loading, testing, and integrating ready-made models into applications.
• Creating your own models using Create ML — without needing to write code in Python.
• Natural Language processing (Natural Language framework): text analysis, language recognition, sentiment analysis.
• Computer vision: image classification, object detection with Vision and Core ML.
• Optimizing models for mobile devices: compression, quantization, memory management.
• Integration with MLKit, TensorFlow Lite, and other third-party tools.
• Real-world cases: recommendation systems, predictive keyboards, photo filters.

Who is this book for?

• iOS/macOS developers looking to add ML features to their projects.
• Beginning Data Science specialists who want to deploy models on mobile platforms.
• Students and educators studying modern approaches to machine learning in Swift.

What will you learn?

• How to prepare data for training a model in Swift.
• How to convert models from Python (Keras, PyTorch) to the Core ML format.
• How to build an end-to-end pipeline: from data collection to publishing in the App Store.
• How to test model performance on real devices.
• How to use Combine and SwiftUI to display ML results in real time.

The book is written in accessible language and contains numerous code examples and practical exercises. All projects can be downloaded and run on your Mac. You will learn not only how to use ready-made solutions but also how to create your own ML models optimized for the Apple ecosystem.

This edition is suitable for both beginners in machine learning and experienced developers who want to expand their technology stack. After reading, you will be able to confidently apply machine learning in commercial applications for iOS and macOS.