Applied natural language processing (34 Ergebnisse)

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Paperback. Zustand: Very Good. Reference and Computation: An Essay in Applied Philosophy of Language (Studies in Natural Language Processing) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. …

Paperback. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.

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.…

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: Used. pp. 240.

Zustand: Used. pp. 240.

Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Paperback. Zustand: Very Good. Zustand des Schutzumschlags: No d/j as Published. Type: Book N.B. Small label to inside front cover. Light rubbing to edges and corners of covers.

Zustand: New. In English.

Zustand: Good. Good condition.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Neuware - Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: - Build scalable NLP and text analytics workflows for enterprise data- Apply deep learning architectures, attention mechanisms, and transformers to text- Develop named entity recognition and information extraction systems- Perform sentiment analysis and topic modeling across large text collections- Build semantic search systems using document embeddings and vector databases- Design Retrieval-Augmented Generation (RAG) systems grounded in organizational data- Understand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniques- Adapt NLP and LLM solutions for specialized domains and business workflows- Integrate AI models through enterprise APIs and automated processes- Evaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has.…

Zustand: New. In English.

Paperback. Zustand: Brand New. 150 pages. 9.00x6.00x0.25 inches. In Stock.

Zustand: New. 2018. 1st ed. Paperback. . . . . . Books ship from the US and Ireland.

Zustand: New. A text which deals with two major problems in the study of language. First, how do we successfully refer to objects in conversation. Second, how can a computer be programmed to simulate this ability? The author outlines an answer to these questions. Series Editor(s): Bird, Steven; HIndle, Don; Kay, Martin; McDonald, David; Uszkoreit, Hans; Wilks, Yorick. Series: Studies in Natural Language Processing. Num Pages: 208 pages, figures, references, index. BIC Classification: CFX. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 12. Weight in Grams: 310. . 1990. paperback. . . . . Books ship from the US and Ireland. …

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Neuware - Unlock the Power of PyTorch 2.0 for Next-Level Natural Language Processing.

Paperback. Zustand: Brand New. 350 pages. 9.19x7.00x0.70 inches. In Stock.

Zustand: New.

Zustand: New. In English.

Zustand: New. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With some Python experience and a basic understanding of machine learning, you ll learn how to build and deploy real-world NLP applications in your organization.

Taschenbuch. Zustand: Neu. Neuware - NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.- Understand how state-of-the-art NLP models work- Learn the tools of the trade, including frameworks popular today- Perform NLP tasks such as text classification, semantic search, and reading comprehension- Solve problems using new models like transformers and techniques such as transfer learning- Build NLP models from scratch with performance comparable or superior to out-of-the-box systems- Deploy your models to production and maintain their performance- Implement a suite of NLP algorithms using Python and PyTorch.…

Zustand: New. 2021. Paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Zustand: Neu. Applied Natural Language Processing with Python | Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing | Taweh Beysolow Ii | Taschenbuch | xv | Englisch | 2018 | Apress | EAN 9781484237328 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Zustand: Gut. Zustand: Gut | Seiten: 333 | Sprache: Englisch | Produktart: Bücher | NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP applications. This hands-on guide helps you learn the process quickly.If you have a basic to intermediate understanding of machine learning and programming experience with Python, you'll learn how to build and deploy real-world NLP applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai walk you through the process without bogging you down in theory.Understand how state-of-the-art NLP models workLearn the tools of the trade, including frameworks popular todayPerform NLP tasks such as text classification, semantic search, and reading comprehensionSolve problems using new models like transformers and techniques such as transfer learningBuild NLP models from scratch with performance comparable or superior to out-of-the-box systemsDeploy your models to production and maintain their performanceImplement a suite of NLP algorithms using Python and PyTorch.…