yankai (25 Ergebnisse)

hardcover. Zustand: Very Good.

hardcover. Zustand: Good. Book is bent.

Zustand: New. In.

Hardcover. Zustand: Very Good. 1st ed. 2020. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

1st ed. 2020. XXIII, 245 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Zustand: New. In.

Zustand: New. In.

Zustand: New. In.

Paperback. Zustand: Brand New. 2nd edition. 541 pages. 9.25x6.10x1.10 inches. In Stock.

Hardcover. Zustand: Brand New. 2nd edition. 541 pages. 9.25x6.10x1.34 inches. In Stock.

Hardcover. Zustand: Very Good. 1. Auflage. Unread, cover with shelfwear or minor damages. Immediately dispatched from Germany.

Taschenbuch. Zustand: Neu. Representation Learning for Natural Language Processing | Zhiyuan Liu (u. a.) | Taschenbuch | xx | Englisch | 2023 | Springer | EAN 9789819916023 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.

Zustand: New. In English.

Zustand: New. In English.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 544 | Sprache: Englisch | Produktart: Bücher | This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 544 | Sprache: Englisch | Produktart: Bücher | This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions.The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, socialnetwork analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.As compared to the first edition, the second edition (1) provides a more detailed introduction to representation learning in Chapter 1; (2) adds four new chapters to introduce pre-trained language models, robust representation learning, legal knowledge representation learning and biomedical knowledge representation learning; (3) updates recent advances in representation learning in all chapters; and (4) corrects some errors in the first edition. The new contents will be approximately 50%+ compared to the first edition. This is an open access book.

Paperback. Zustand: Brand New. 272 pages. 9.25x6.10x0.64 inches. In Stock.

Zustand: New. In.

Hardcover. Zustand: Brand New. 268 pages. 9.25x6.10x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Early-life Environmental Exposure and Disease | Facts and Perspectives | Yankai Xia | Taschenbuch | xvi | Englisch | 2021 | Springer | EAN 9789811537998 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers valuable insights into the latest concepts and findings from epidemiologic, clinical and basic studies in the burgeoning area of early-life environmental exposure and diseases. The book is divided into five parts, starting with an overview of environmental exposure measurement and evaluation, followed by a review of the effects of exposure to various substances like tobacco smoke, pesticides and metals as well as stress on offspring's health. It then discusses the developmental origins of a range of childhood diseases that affect growth, neural development and the immune system, and highlights the importance of longitudinal studies that measure exposure at potentially sensitive time points during childhood. It also provides up-to-date evidence of the intergenerational/transgenerational effects of early-life environmental exposure, especially via genetic and epigenetic pathways. Allowing readers to gain a thorough understanding of the predominating aspects of early-life environmental exposure and diseases, the book also provides a basis for developing environmental and health policies that could have wide and long-term impacts on human health.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers valuable insights into the latest concepts and findings from epidemiologic, clinical and basic studies in the burgeoning area of early-life environmental exposure and diseases. The book is divided into five parts, starting with an overview of environmental exposure measurement and evaluation, followed by a review of the effects of exposure to various substances like tobacco smoke, pesticides and metals as well as stress on offspring's health. It then discusses the developmental origins of a range of childhood diseases that affect growth, neural development and the immune system, and highlights the importance of longitudinal studies that measure exposure at potentially sensitive time points during childhood. It also provides up-to-date evidence of the intergenerational/transgenerational effects of early-life environmental exposure, especially via genetic and epigenetic pathways. Allowing readers to gain a thorough understanding of the predominating aspects of early-life environmental exposure and diseases, the book also provides a basis for developing environmental and health policies that could have wide and long-term impacts on human health.

Hardcover. Zustand: Brand New. 1st edition. 239 pages. 9.25x6.25x0.75 inches. In Stock.