Explore the advanced framework of text analytics with 'Machine Learning for Text', the second edition textbook by Charu C. Aggarwal. This comprehensive guide integrates information retrieval, machine learning, and natural language processing, with a significant focus on deep learning methods. It covers basic algorithms like preprocessing, topic modeling, and classification, alongside domain-sensitive learning and information retrieval. Delve into natural language processing applications including neural language models, transformers, knowledge graphs, and question answering. Ideal for advanced computer science and math students, this hardcover book offers substantial new material on cutting-edge NLP topics. Key Features: * Covers basic algorithms, domain-sensitive learning, and natural language processing. * Emphasizes deep learning, transformers, and pre-trained language models. * Integrates information retrieval, machine learning, and NLP concepts. Summary: Machine Learning for Text by Charu C. Aggarwal, ISBN 9783030966225. This first edition English hardcover book has 565 pages and was published by Springer Cham on 05/05/2022.