Applied Natural Language Processing in the Enterprise

NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.Understand how state-of-the-art NLP models workLearn the tools of the trade, including frameworks popular todayPerform NLP tasks such as text classification, semantic search, and reading comprehensionSolve problems using new models like transformers and techniques such as transfer learningBuild NLP models from scratch with performance comparable or superior to out-of-the-box systemsDeploy your models to production and maintain their performanceImplement a suite of NLP algorithms using Python and PyTorch