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Practical Natural Language Processing
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey.
Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail.
With this book, you’ll:
Understand the wide spectrum of problem statements, tasks, and solution approaches within NLPImplement and evaluate different NLP applications using machine learning and deep learning methodsFine-tune your NLP solution based on your business problem and industry verticalEvaluate various algorithms and approaches for NLP product tasks, datasets, and stagesProduce software solutions following best practices around release, deployment, and DevOps for NLP systemsUnderstand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
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