AI Design Patterns for Information Professionals

Welcome

About This Book

Note

This is a work in progress. Content will be added and updated over time. This is an early draft!

This book documents practical AI design patterns for information professionals — librarians, archivists, journalists, charity analysts, records managers, and anyone working with large collections of documents or data without a dedicated machine learning team.

If you work with large collections of text, images, or records and want to use AI to extract, organize, or enrich that information — but don’t have an ML engineering team — this book is for you. The examples come from (Galleries, Libraries, Archives, and Museums) and specifically from work with the National Library of Scotland, but the patterns apply to any information-rich organisation working with collections at scale.

About the Author

Daniel van Strien is a Machine Learning Librarian at Hugging Face, where he focuses on datasets and building bridges between machine learning and the cultural heritage sector. Before moving into ML, he worked as a librarian and digital curator at the British Library and other institutions. This combination of library practice and machine learning informs the approach taken in this book: practical, sustainable, and grounded in the realities of working with collections at scale.