learning machine translation (138 Ergebnisse)

Hardcover. Zustand: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.86.

Zustand: New. pp.218.

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Soft cover. Zustand: New. ISBN:9781788398060,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.

Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days. 360.

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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 199 | Sprache: Englisch | Produktart: Bücher.

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Regression based machine translation (RegMT) model provides a learning framework for machine translation, separating learning models for training, training instance selection, feature representation, and decoding. Transductive learning approach employs training instance selection algorithms that not only make RegMT computationally more scalable but also improve the performance of standard statistical machine translation (SMT) systems. Sparse regression models for SMT are introduced and the obtained results demonstrate that sparse regression models perform better than other learning models in predicting target features, estimating word alignments, creating phrase tables, and generating translation outputs. We develop good evaluation techniques for measuring the performance of the RegMT model and the quality of the translations. We demonstrate that sparse L1 regularized regression performs better than L2 regularized regression in the German-English translation task and in the Spanish-English translation task when using small sized training sets. Graph based decoding can provide an alternative to phrase-based decoding in translation domains having low vocabulary.

Taschenbuch. Zustand: Neu. Neuware -The book investigates how machine translation (MT) provides opportunities and increases the willingness to communicate in a foreign language. It is informed by a mixed methods methodological approach that analyzes quantitative and qualitative data of questionnaires and real-time instant messages (IM). The book is unique because it contains tables, figures, and screenshots of actual real-time IM exchanges. It is innovative in discussing IM translation, a novel form of MT, and demonstrates how the technology offers English foreign language learners, in this case, Chinese college students, communication opportunities while increasing their willingness to communicate. The study provides an interesting insight into IM user profiles, clients, and usages. Smartphone screenshots are the locale of the study whose findings have far-reaching implications for students, language and translation instructors, and curriculum designers.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 200 pp. Englisch.

Hardback. Zustand: New. New copy - Usually dispatched within 4 working days. 185.

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paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2014-12-1 Publisher: Science Press This book is an extension of the top international academic conference in 2006 NIPS (NeuralInformationProcessingSystemsConference) published an article together. divided into two parts. The first part is a machine translation research describes the latest developments. including the translation model. a parallel corpus and name mining entities. the application of nuclear methods; the second part is a senior statistical m.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2018-12-01 Publisher: Mechanical Industry Press This book introduces the workflow of practical machine learning. which is mainly described from a practical perspective. without mathematical formulas and derivations. This book covers data collection and processing. model building. evaluation and optimization. feature recognition. extraction and selection techniques. advanced feature engineering. data visualization techniques. and model deployment.