Deep Natural Language Processing and AI Applications for Industry 5.0, Tanwar Poonam, Saxena Arti, Priya C.
Автор: Maosong Sun, Xiaojie Wang, Baobao Chang Название: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data ISBN: 3319690043 ISBN-13(EAN): 9783319690049 Издательство: Springer Рейтинг: Цена: 5300.00 р. Наличие на складе: Есть (3 шт.) Описание: This book constitutes the proceedings of the 16th China National Conference on Computational Linguistics, CCL 2017, and the 5th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2017, held in Nanjing, China, in October 2017. Minority language information processing.
Описание: Developers working with NLP will be able to put their knowledge to work with this practical guide to PyTorch. You will learn to use PyTorch offerings and how to understand and analyze text using Python. You will learn to extract the underlying meaning in the text using deep neural networks and modern deep learning algorithms.
Описание: This book constitutes the refereed proceedings of the 11th International Conference, NooJ 2017, held in Kenitra and Rabat, Morocco, in May 2017. The 20 revised full papers presented in this volume were carefully reviewed and selected from 56 submissions.
Описание: NooJ provides linguists with tools to develop dictionaries, regular grammars, context-free grammars, context-sensitive grammars and unrestricted grammars as well as their graphical equivalent to formalize each linguistic phenomenon.
One-stop solution for NLP practitioners, ML developers and data scientists to build effective NLP systems that can perform real-world complicated tasks
Key Features
Implement deep learning algorithms such as BiLSTMS, CRFs, and many more using TensorFlow 2
Explore classical NLP techniques and libraries including parts-of-speech tagging and tokenization
Learn practical applications of NLP covering the forefronts of the field like sentiment analysis and generating text
Book Description
In the last couple of years, there have been tremendous advances in natural language processing, and we are now moving from research labs into practical applications. Advanced Natural Language Processing comes with a perfect blend of both the theoretical and practical aspects of trending and complex NLP techniques.
This book is focused on innovative applications in the field of NLP, language generation, and dialogue systems. It goes into the details of applying the concepts of text pre-processing using techniques such as tokenization, parts of speech tagging, and lemmatization using popular libraries such as Stanford NLP and SpaCy. Named Entity Recognition (NER), a cornerstone of task-oriented bots, is built from scratch using Conditional Random Fields and Viterbi Decoding on top of RNNs.
Taking a practical and application-focused perspective, the book covers key emerging areas such as generating text for use in sentence completion and text summarization, bridging images and text by generating captions for images, and managing dialogue aspects of chatbot design. It also covers one of the most important reasons behind recent advances in NLP - applying transfer learning and fine-tuning using TensorFlow 2.
Further, it covers practical techniques that can simplify the labelling of textual data which otherwise proves to be a costly affair. The book also has a working code for each tech piece so that you can adapt them to your use cases.
By the end of this TensorFlow book, you will have an advanced knowledge of the tools, techniques and deep learning architecture used to solve complex NLP problems.
What You Will Learn
Grasp important pre-steps in building NLP applications like POS tagging
Deal with vast amounts of unlabeled and small labelled Datasets in NLP
Use transfer and weakly supervised learning using libraries like Snorkel
Perform sentiment analysis using BERT
Apply encoder-decoder NN architectures and beam search for summarizing text
Use transformer models with attention to bring images and text together
Build applications that generate captions and answer questions about images
Use advanced TensorFlow techniques like learning rate annealing, custom layers, and custom loss functions to build the latest deep NLP models
Who this book is for
This is not an introductory book and assumes the reader is familiar with basics of NLP and has fundamental Python skills, as well as basic knowledge of machine learning and undergraduate-level calculus and linear algebra.
The readers who can benefit the most from this book include:
Intermediate ML developers who are familiar with the basics of supervised learning and deep learning techniques
Professionals who already use TensorFlow/Python for purposes such as data science, ML, research, and analysis
Описание: Get hands-on knowledge of how BERT (Bidirectional Encoder Representations from Transformers) can be used to develop question answering (QA) systems by using natural language processing (NLP) and deep learning. The book begins with an overview of the technology landscape behind BERT.
Описание: This book constitutes the refereed proceedings of the 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, held in Saarbrucken, Germany, in June 2020.*The 15 full papers and 10 short papers were carefully reviewed and selected from 68 submissions.
Автор: Lalitha Devi Sobha; Ant?nio Branco; Ruslan Mitkov Название: Anaphora Processing and Applications ISBN: 3642049745 ISBN-13(EAN): 9783642049743 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Distribution of anaphora in natural language and the complexity of its resolution have resulted in a wide range of disciplines focusing their research on this grammatical phenomenon.
Автор: Li Deng; Yang Liu Название: Deep Learning in Natural Language Processing ISBN: 9811052085 ISBN-13(EAN): 9789811052088 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Автор: Tanwar Poonam, Saxena Arti, Priya C. Название: Deep Natural Language Processing and AI Applications for Industry 5.0 ISBN: 1799877280 ISBN-13(EAN): 9781799877288 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 39085.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer's life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions.
Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students.
Описание: If you`re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.
Автор: Khaled Shaalan; Aboul Ella Hassanien; Fahmy Tolba Название: Intelligent Natural Language Processing: Trends and Applications ISBN: 3319670557 ISBN-13(EAN): 9783319670553 Издательство: Springer Рейтинг: Цена: 34937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Features Extraction and On-Line Recognition of Isolated Arabic Characters.- Using Text Mining Techniques for Extracting Information from Research Articles.- Authorship and Time Attribution of Arabic Texts Using JGAAP.- TALAA-ATSF: A Global Operation-Based Arabic Text Summarization Framework.- e="Calibri">An Evaluation of the Morphological Analysis of Egyptian Arabic TreeBank.- Alserag: An Automatic Diacritization System for Arabic.- font-size:11.0pt; line-height:107%;font-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri;mso-fareast-theme-font: minor-latin;mso-hansi-theme-font: minor-latin;mso-bidi-font-family: Arial;mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US;mso-fareast-language: EN-US;mso-bidi-language: AR-SA">Developing a Transfer-based System for Arabic Dialects Translation.- Education and Knowledge Based Augmented Reality (AR).- 7%;font-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-familyText Mining and Analytics: A Case Study from Channels Posts on Facebook.- A New Semantic Distance Measure for the VSM-Based Information Retrieval Systems.-family: "Calibri","sans-serif";mso-ascii-theme-font: minor-latin; mso-fareast-font-family: Calibri;mso-fareast-theme-font: minor-latin;mso-hansi-theme-font: minor-latin;mso-bidi-font-family: Arial;mso-bidi-theme-font: minor-bidi; mso-ansi-language: EN-US;mso-fareast-language: EN-US;mso-bidi-language: AR-SA">
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