2021 | English | 9781098108649 | EPUB | 36 pages | 1.26 MB
Organizations in all industries are increasingly finding ways to leverage the information hidden in natural language to solve customer service issues, get insights from product reviews and medical records, and so much more. These insights depend on the ability of machines to understand and generate natural language.
So how can your organization implement natural language processing (NLP) solutions for business problems in a smart, strategic way? With this report, department and data science team leaders walk through four enterprise use cases involving real companies. If you own the implementation of a project involving text analytics and NLP, you'll learn about the workflows, challenges, and key lessons learned that enabled each of these companies to get impactful results.
Author Kinga Parrott, a senior AI strategy leader, discusses the critical importance of setting up the annotation process to transfer subject matter expertise to AI systems in NLP projects. You will learn when to set up the annotation process, how to effectively engage subject matter experts, and common pitfalls to avoid.
Use cases in this report cover the following business needs
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