Natural language processing using (123 Ergebnisse)

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Paperback. Zustand: Very Good. Natural Language Processing Crash Course for BeginnersArtificial Intelligence (AI) isn't the latest fad The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings.How Is This Book Different?This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder.The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning.Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing?Environment Setup and Python Crash CourseIntroduction to Deep LearningText Cleaning and ManipulationCommon NLP TasksImporting Text Data from Various SourcesWord Embeddings: Converting Words to NumbersIMDB Movies Sentimental AnalysisHam and Spam Message ClassificationText Summarization and Topic ModelingText Classification with Deep LearningText Translation Using Seq2Seq ModelState of the Art NLP with BERT TransformersHands-on NLP Projects/Articles for PracticeExercise SolutionsClick the BUY button and download the book now to start your Natural Language Processing journey.…

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Zustand: New. In English.

Zustand: New. In English.

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Zustand: very good. Cambridge, MA: The MIT Press, 1994. Paperback. 359 pp.(ACL-MIT Series in Natural Language Processing). -Today, large corpora consisting of hundreds of millions or even billions of words, along with new empirical and statistical methods for organizing and analyzing these data, promise new insights into the use of language. Already, the data extracted from these large corpora reveal that language use is more flexible and complex than most rule-based systems have tried to account for, providing a basis for progress in the performance of Natural Language Processing systems. Using Large Corpora identifies these new data-oriented methods and describes the potential results that the use of large corpora offers.The research described shows that the new methods may offer solutions to key issues of acquisition (automatically identifying and coding information), coverage (accounting for all of the phenomena in a given domain), robustness (accommodating "real data" that may be corrupt or not accounted for in the model), and extensibility (applying the model and data to a new domain, text, or problem). There are chapters on lexical issues, issues in syntax, and translation topics, as well discussions of the "statistics-based" vs. "rule-based" debate.ACL-MIT Series in Natural Language ProcessingEnglish text. Condition : very good. Condition : very good copy. ISBN 9780262510820. Keywords : LINGUISTICS. …

Zustand: as new. Cambridge, MA : The MIT Press, 2010. Hardcover. Dustjacket. 512 pp.- The last decade has seen computational implementations of large hand-crafted natural language grammars in formal frameworks such as Tree-Adjoining Grammar (TAG), Combinatory Categorical Grammar (CCG), Head-driven Phrase Structure Grammar (HPSG), and Lexical Functional Grammar (LFG). Grammars in these frameworks typically associate linguistically motivated rich descriptions (Supertags) with words. With the availability of parse-annotated corpora, grammars in the TAG and CCG frameworks have also been automatically extracted while maintaining the linguistic relevance of the extracted Supertags. In these frameworks, Supertags are designed so that complex linguistic constraints are localized to operate within the domain of those descriptions. While this localization increases local ambiguity, the process of disambiguation (Supertagging) provides a unique way of combining linguistic and statistical information. This volume investigates the theme of employing statistical approaches with linguistically motivated representations and its impact on Natural Language Processing tasks. In particular, the contributors describe research in which words are associated with Supertags that are the primitives of different grammar formalisms including Lexicalized Tree-Adjoining Grammar (LTAG). ContributorsJens Bäcker, Srinivas Bangalore, Akshar Bharati, Pierre Boullier, Tomas By, John Chen, Stephen Clark, Berthold Crysmann, James R. Curran, Kilian Foth, Robert Frank, Karin Harbusch, Sa?a Hasan, Aravind Joshi,Vincenzo Lombardo, Takuya Matsuzaki, Alessandro Mazzei, Wolfgang Menzel, Yusuke Miyao, Richard Moot, Alexis Nasr, Günter Neumann, Martha Palmer, Owen Rambow, Rajeev Sangal, Anoop Sarkar, Giorgio Satta, Libin Shen, Patrick Sturt, Jun'ichi Tsujii, K. Vijay-Shanker, Wen Wang, Fei XiaEnglish text. Condition : a Condition : as new copy. ISBN 9780262013871. Keywords : .…

Paperback. Zustand: Brand New. 300 pages. 8.75x6.00x0.50 inches. In Stock.

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Zustand: New. In English.

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