Text Annotation Handbook: A Practical Guide for Machine Learning Projects
It addresses the need for clear, practical guidance on text annotation for team leaders, project managers, and engineers in machine learning projects, though it is incremental as it compiles existing knowledge into a handbook format.
The handbook tackles the practical challenges of text annotation for machine learning projects by providing a comprehensive guide that covers theoretical concepts, technical topics, and business considerations, aiming to serve as an accessible primer for various professionals.
This handbook is a hands-on guide on how to approach text annotation tasks. It provides a gentle introduction to the topic, an overview of theoretical concepts as well as practical advice. The topics covered are mostly technical, but business, ethical and regulatory issues are also touched upon. The focus lies on readability and conciseness rather than completeness and scientific rigor. Experience with annotation and knowledge of machine learning are useful but not required. The document may serve as a primer or reference book for a wide range of professions such as team leaders, project managers, IT architects, software developers and machine learning engineers.