Practical Natural Language Processing

A guide for software engineers and data scientists explains how to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, covering such topics as problem statements, tasks, and solution approaches within NLP, implementing different NLP applications using machine learning and deep learning methods, and evaluating various algorithms and approaches for NLP product tasks, datasets, and stages.