With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Yue Zhang is an associate professor at Westlake University. Before joining Westlake, he worked as a research associate at the University of Cambridge and then a faculty member at Singapore University of Technology and Design. His research interests lie in fundamental algorithms for NLP, syntax, semantics, information extraction, text generation, and machine translation. He serves as an action editor for TACL, and as area chairs of ACL, EMNLP, COLING, and NAACL. He gave several tutorials at ACL, EMNLP and NAACL, and won a best paper award at COLING in 2018.
Zhiyang Teng is currently a postdoctoral research fellow in the natural language processing group of Westlake University, China. He obtained his Ph.D. from Singapore University of Technology and Design (SUTD) in 2018, and his Master's from the University of Chinese Academy of Science in 2014. He won the best paper award at CCL/NLP-NABD 2014, and published conference papers for ACL/TACL, EMNLP, COLING, NAACL, and TKDE. His research interests include syntactic parsing, sentiment analysis, deep learning, and variational inference.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: WeBuyBooks, Rossendale, LANCS, Vereinigtes Königreich
Zustand: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind. Bestandsnummer des Verkäufers wbs4483737341
Anzahl: 1 verfügbar
Anbieter: GoldBooks, Denver, CO, USA
Zustand: new. Bestandsnummer des Verkäufers 10T72_56_1108420214
Anzahl: 1 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: New. Bestandsnummer des Verkäufers 41852623-n
Anzahl: 2 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Bestandsnummer des Verkäufers GB-9781108420211
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Bestandsnummer des Verkäufers GB-9781108420211
Anzahl: 1 verfügbar
Anbieter: Lucky's Textbooks, Dallas, TX, USA
Zustand: New. Bestandsnummer des Verkäufers ABLIING23Mar2317530282428
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPrices, Columbia, MD, USA
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 41852623
Anzahl: 2 verfügbar
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9781108420211
Anzahl: Mehr als 20 verfügbar
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
Zustand: New. Bestandsnummer des Verkäufers 41852623-n
Anzahl: 2 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9781108420211_new
Anzahl: 1 verfügbar