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Natural language understanding (NLU) is a technology that structures language so that computer systems can further process it to perform useful applications. Developers will find that this practical guide enables them to use NLU techniques to develop many kinds of NLU applications, and managers will be able to identify areas where NLU can be applied to solve real problems in their enterprises. Complete with step-by-step explanations of essential concepts and practical examples, you will begin by learning what NLU is and how it can be applied. You will then learn about the wide range of current NLU techniques, and you will learn about the best situations to apply each one, including the new large language models (LLMs). In the process, you will be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, but you will also learn about many practical issues such as acquiring data, evaluating systems, improving your system’s results, and deploying NLU applications. Most importantly, you will not just learn a rote list of techniques, but you will learn how to take advantage of the vast number of NLU resources on the web in your future work. Python developers who are interested in learning about NLU and applying natural language processing (NLP) technology to real problems will get the most from this book, including computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students of these topics. The earlier chapters will also be interesting for non-technical project managers. Working knowledge of Python is required to get the best from this book. You do not need any previous knowledge of NLU.