a gentle introduction Surdeanu, Mihai creator author. Valenzuela-Escárcega, Marco Antonio author. text si Singapore Cambridge University Press c2024 2024 monographic eng xviii, 325 pages : illustrations (black and white) ; 23 cm. "Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems." --Provided by the publisher Contents: List of figures — List of Tables — Preface — 1 Introduction — 2 The perception — 3 Logistic regression — 4 Implementing text classification using perception and logistic — 5 Feed-Forward neural networks — 6 Best practices in deep learning — 7 Implementing text classification — 8 Distributional hypothesis and representation learning — 9 Implementing text classification using word — 10 Recurrent neural networks — 11 Implementing part-of-speech tagging using recurrent neural networks — 12 Contextualized embeddings and transformer networks — 13. Using transformers with the hugging face library — 14. Encoder-decoder methods — 15.Implementing Encoder-decoder methods — 16. Neural architectures for natural language processing — Appendix A Overview of the python language and key — Appendix B Character encodings: ASCII and Unicode — References — Index. Adult adult Mihai Surdeanu and Marco Antonio Valezuela-Escárcega. Includes bibliographical references and index. Published Ortega, Eric College of Computer Studies Computer Science Text in English Natural language processing (Computer science) Deep learning (Machine learning) Neural networks (Computer science) Computational linguistics 9781009012652 [paperback] University of Cebu-Banilad 260702 20260702142954.0