Swift (iOS/macOS) for Data Science: Machine Learning and Data Analysis on Apple

The book "Swift (iOS/macOS) for Data Science" is the first practical guide in Russian that opens the world of data analysis and machine learning for Apple ecosystem developers. Contrary to the stereotype that Data Science is only Python and R, Swift is becoming a powerful tool for working with data, especially in the context of mobile and desktop applications.

What is this book about?

The book covers the complete data workflow in Swift: from collection and cleaning to building and deploying machine learning models. You will learn how to use Apple frameworks (Core ML, Create ML, Vision, Natural Language) and third-party libraries (Swift for TensorFlow, NumPy-like arrays, visualization libraries).

Who is this book for?

• iOS/macOS developers who want to add ML features to their applications
• Data Scientists interested in alternative tools and the Apple platform
• Students and beginners looking to learn Data Science with modern languages
• Product managers and technical leaders evaluating Swift's capabilities for analytics

What will you learn?

• Data fundamentals: parsing CSV/JSON, handling missing values, normalization
• Numerical computing in Swift: arrays, matrices, statistical functions
• Data visualization using Swift Charts and third-party libraries
• Creating machine learning models with Create ML without deep mathematical knowledge
• Integrating ready-made Core ML models into iOS/macOS applications
• Working with images and text: classification, object detection, NLP
• Deploying models on Apple devices with consideration for performance and privacy
• Practical projects: recommendation system, sentiment analyzer, anomaly detector

Why Swift for Data Science?

Swift combines the high performance of a compiled language with expressive syntax. In the Apple ecosystem, it provides:

• Native integration with hardware acceleration (GPU, Neural Engine)
• Type safety and memory management without a garbage collector
• The ability to run models directly on the device (on-device ML)
• A unified codebase for iOS, macOS, watchOS, and tvOS

The book contains numerous code examples ready to use in Xcode. Each chapter concludes with practical exercises to reinforce the material. Regardless of your current level, you will be able to apply the knowledge gained to create intelligent applications for Apple platforms.

Discover Swift as a full-fledged Data Science tool — from simple analysis to complex neural networks on your iPhone or Mac.