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Statistical machine translation, Koehn, Philipp



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Автор: Koehn, Philipp
Название:  Statistical machine translation
Перевод названия: Филипп Коэн: Машинный перевод на основе статистик
ISBN: 9780521874151
Издательство: Cambridge Academ
Классификация:
ISBN-10: 0521874157
Обложка/Формат: Hardback
Страницы: 488
Вес: 0.954 кг.
Дата издания: 31.10.2009
Язык: English
Иллюстрации: 24 b/w illus. 70 exercises
Размер: 254 x 180 x 26
Читательская аудитория: Tertiary education (us: college)
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Automatic language translation systems like those used by Google, have been revolutionized by recent advances in the methods used in statistical machine translation. This first textbook on the topic explains these innovations carefully and shows the reader, whether a student or a developer, how to build their own translation system.



Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Цена: 11878 р.
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Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 18622 р.
Наличие на складе: Ожидается поступление.

Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Handbook of Natural Language Processing and Machine Translation

Автор: Joseph Olive, Caitlin Christianson, John McCary
Название: Handbook of Natural Language Processing and Machine Translation
ISBN: 1441977120 ISBN-13(EAN): 9781441977120
Издательство: Springer
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Цена: 34937 р.
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Описание: This comprehensive handbook, written by leading experts in the field, details the groundbreaking research conducted under the breakthrough GALE program--The Global Autonomous Language Exploitation within the Defense Advanced Research Projects Agency (DARPA), while placing it in the context of previous research in the fields of natural language and signal processing, artificial intelligence and machine translation.The most fundamental contrast between GALE and its predecessor programs was its holistic integration of previously separate or sequential processes. In earlier language research programs, each of the individual processes was performed separately and sequentially: speech recognition, language recognition, transcription, translation, and content summarization. The GALE program employed a distinctly new approach by executing these processes simultaneously. Speech and language recognition algorithms now aid translation and transcription processes and vice versa. This combination of previously distinct processes has produced significant research and performance breakthroughs and has fundamentally changed the natural language processing and machine translation fields.This comprehensive handbook provides an exhaustive exploration into these latest technologies in natural language, speech and signal processing, and machine translation, providing researchers, practitioners and students with an authoritative reference on the topic.

Conference Interpreting Explained (Translation Practices Explained)

Автор: Jones
Название: Conference Interpreting Explained (Translation Practices Explained)
ISBN: 1900650576 ISBN-13(EAN): 9781900650571
Издательство: Taylor&Francis
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Цена: 4355 р.
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Описание: Roderick Jones adopts a very practical approach to both consecutive and simultaneous interpreting, providing detailed illustrations of note-taking, reformulation, the `salami` technique, simplification, generalization, anticipation, and so on

The Translation Studies Reader

Автор: Ed. by L. Venuti
Название: The Translation Studies Reader
ISBN: 0415187478 ISBN-13(EAN): 9780415187473
Издательство: Taylor&Francis
Цена: 3048 р.
Наличие на складе: Поставка под заказ.

Описание: This text guides the reader through the varying approaches to translation studies in the latter half of the 20th century. Chronologically ordered and divided into clear sections, Lawrence Venuti has gathered key essays, articles and book extracts together in one volume, thus providing a clear history of translation studies. The text also covers contemporary translation research and analysis, and, as it approaches the end of the 20th century, offers glimpses of possible future trends. Venuti introduces each section with comments on the readings and influential theorists, sketches the main theoretical trends in the period and offers critical assessment. Tbook should be useful as a course textbook and a stimulus for further research.

Introduction to Statistical Machine Learning

Автор: Masashi Sugiyama
Название: Introduction to Statistical Machine Learning
ISBN: 0128021217 ISBN-13(EAN): 9780128021217
Издательство: Elsevier Science
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Цена: 14345 р.
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Описание:

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials.

Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks.

  • Provides the necessary background material to understand machine learning such as statistics, probability, linear algebra, and calculus
  • Complete coverage of the generative approach to statistical pattern recognition and the discriminative approach to statistical machine learning
  • Includes MATLAB/Octave programs so that readers can test the algorithms numerically and acquire both mathematical and practical skills in a wide range of data analysis tasks
  • Discusses a wide range of applications in machine learning and statistics and provides examples drawn from image processing, speech processing, natural language processing, robot control, as well as biology, medicine, astronomy, physics, and materials
Introduction to Machine Learning with Applications in Information Security

Автор: Stamp
Название: Introduction to Machine Learning with Applications in Information Security
ISBN: 1138626783 ISBN-13(EAN): 9781138626782
Издательство: Taylor&Francis
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Цена: 8275 р.
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Описание: This class-tested textbook will provide in-depth coverage of the fundamentals of machine learning, with an exploration of applications in information security. The book will cover malware detection, cryptography, and intrusion detection. The book will be relevant for students in machine learning and computer security courses.

Statistical Methods for Recommender Systems

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 7285 р.
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Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.

Machine Learning

Автор: Marsland
Название: Machine Learning
ISBN: 1466583282 ISBN-13(EAN): 9781466583283
Издательство: Taylor&Francis
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Цена: 10889 р.
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Описание:

A Proven, Hands-On Approach for Students without a Strong Statistical Foundation

Since the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area.

Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.

New to the Second Edition

  • Two new chapters on deep belief networks and Gaussian processes
  • Reorganization of the chapters to make a more natural flow of content
  • Revision of the support vector machine material, including a simple implementation for experiments
  • New material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptron
  • Additional discussions of the Kalman and particle filters
  • Improved code, including better use of naming conventions in Python

Suitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and problems. All of the code used to create the examples is available on the author's website.

A First Course in Machine Learning, Second Edition

Автор: Rogers
Название: A First Course in Machine Learning, Second Edition
ISBN: 1498738486 ISBN-13(EAN): 9781498738484
Издательство: Taylor&Francis
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Цена: 9437 р.
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Описание: The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.

Hybrid Approaches to Machine Translation

Автор: Costa-juss?
Название: Hybrid Approaches to Machine Translation
ISBN: 3319213105 ISBN-13(EAN): 9783319213101
Издательство: Springer
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Цена: 11878 р.
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Описание: This volume provides an overview of thefield of Hybrid Machine Translation (MT) and presents some of the latestresearch conducted by linguists and practitioners from differentmultidisciplinary areas. Nowadays, most important developments in MT are achievedby combining data-driven and rule-based techniques. These combinationstypically involve hybridization of different traditional paradigms, such as theintroduction of linguistic knowledge into statistical approaches to MT, theincorporation of data-driven components into rule-based approaches, orstatistical and rule-based pre- and post-processing for both types of MTarchitectures.The book is of interest primarily to MTspecialists, but also – in the wider fields of Computational Linguistics,Machine Learning and Data Mining – to translators and managers of translationcompanies and departments who are interested in recent developments concerningautomated translation tools.

Introducing Translation Studies

Автор: Munday Jeremy
Название: Introducing Translation Studies
ISBN: 1138912557 ISBN-13(EAN): 9781138912557
Издательство: Taylor&Francis
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Цена: 4749 р.
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Описание:

Introducing Translation Studies remains the definitive guide to the theories and concepts that make up the field of translation studies. Providing an accessible and up-to-date overview, it has long been the essential textbook on courses worldwide.

This fourth edition has been fully revised and continues to provide a balanced and detailed guide to the theoretical landscape. Each theory is applied to a wide range of languages, including Bengali, Chinese, English, French, German, Italian, Punjabi, Portuguese and Spanish. A broad spectrum of texts is analysed, including the Bible, Buddhist sutras, Beowulf, the fiction of Garcia Marquez and Proust, European Union and UNESCO documents, a range of contemporary films, a travel brochure, a children's cookery book and the translations of Harry Potter.

Each chapter comprises an introduction outlining the translation theory or theories, illustrative texts with translations, case studies, a chapter summary and discussion points and exercises.

NEW FEATURES IN THIS FOURTH EDITION INCLUDE:

  • new material to keep up with developments in research and practice, including the sociology of translation, multilingual cities, translation in the digital age and specialized, audiovisual and machine translation
  • revised discussion points and updated figures and tables
  • new, in-chapter activities with links to online materials and articles to encourage independent research
  • an extensive updated companion website with video introductions and journal articles to accompany each chapter, online exercises, an interactive timeline, weblinks, and powerpoint slides for teacher support

This is a practical, user-friendly textbook ideal for students and researchers on courses in Translation and Translation Studies.


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