Practical Natural Language Processing

Preface

Natural language processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics. It concerns building systems that can process and understand human language. Since its inception in the 1950s and until very recently, NLP has primarily been the domain of academia and research labs, requiring long formal education and training. The past decade’s breakthroughs have resulted in NLP being increasingly used in a range of diverse domains such as retail, healthcare, finance, law, marketing, human resources, and many more. There are a range of driving forces for these developments:

• Widely available and easy-to-use NLP tools, techniques, and APIs are now all-pervading in the industry. There has never been a better time to build quick NLP solutions.
• Development of more interpretable and generalized approaches has improved the baseline performance for even complex NLP tasks, such as open-domain conversational tasks and question answering, which were not practically feasible before.
• More and more organizations, including Google, Microsoft, and Amazon, are investing heavily in more interactive consumer products, where language is used as the primary medium of communication.
• Increased availability of useful open source datasets, along with standard benchmarks on them, has acted as a catalyst in this revolution, as opposed to being impeded by proprietary datasets only available to limited organizations and individuals.
• The viability of NLP ...