Natural Language Processing

Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.
AuthorLewis Tunstall BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP.
AuthorAnkur A. Patel Author 2Ajay Uppili Arasanipalai
All Indian Reprints of O'Reilly are printed in Grayscale If you want to build an enterprise-quality application that uses natural language text but aren't sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. 
AuthorAlex Thomas BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale 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. 
Author 1Sowmya Vajjala Author 2Bodhisattwa Majumder