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The Making And Breaking Of Classification Models In Linguistics

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The Making And Breaking Of Classification Models In Linguistics

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Author : Jane Klavan
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-06-04

The Making And Breaking Of Classification Models In Linguistics written by Jane Klavan and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-04 with Language Arts & Disciplines categories.

The book provides a methodological blueprint for the study of constructional alternations – using corpus-linguistic methods in combination with different types of experimental data. The book looks at a case study from Estonian. This morphologically rich language is typologically different from Indo-European languages such as English. Corpus-based studies allow us to detect patterns in the data and determine what is typical in the language. Experiments are needed to determine the upper and lower limits of human classification behaviour. They give us an idea of what is possible in a language and show how human classification behaviour is susceptible to more variation than corpus-based models lead us to believe. Corpora and forced choice data tell us that when we produce language, we prefer one construction. Acceptability judgement data tell us that when we comprehend language, we judge both constructions as acceptable. The book makes a theoretical contribution to the what, why, and how of constructional alternations.

The Making And Breaking Of Classification Models In Linguistics

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Author : Jane Klavan
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-06-04

Hands On Large Language Models

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Author : Jay Alammar
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-09-11

Hands On Large Language Models written by Jay Alammar and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Computers categories.

AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)

Natural Language Processing

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Author : Yue Zhang
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-07

Natural Language Processing written by Yue Zhang and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with Computers categories.

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

Models In Software Engineering

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Author : Sudipto Ghosh
language : en
Publisher: Springer
Release Date : 2010-04-07

Models In Software Engineering written by Sudipto Ghosh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-07 with Computers categories.

This book constitutes a collection of the best papers selected from 9 workshops and 2 symposia held in conjunction iwth MODELS 2009, the 12 International Conference on Model Driven Engineering Languages and Systems, in Denver, CO, USA, in October 2009. The first two sections contain selected papers from the Doctoral Symposium and the Educational Symposium, respectively. The other contributions are organized according to the workshops at which they were presented: 2nd International Workshop on Model Based Architecting and Construction of Embedded Systems (ACES-MB'09); 14th International Workshop on Aspect-Oriented Modeling (AOM); [email protected] ([email protected]); Model-driven Engineering, Verification, and Validation: Integrating Verification and Validation in MDE (MoDeVVa09); Models and Evolution (MoDSE-MCCM); Third International Workshop on Multi-Paradigm Modeling (MPM09); The Pragmatics of OCL and Other Textual Specification Languages (OCL); 2nd International Workshop on Non-Functional System Properties in Domain Specific Modeling Languages (NFPinDSML); and 2nd Workshop on Transformation and Weaving OWL Ontologies and MDE/MDA (TWOMDE2009). Each section includes a summary of the workshop.

Natural Language Processing With Spark Nlp

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Author : Alex Thomas
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-25

Natural Language Processing With Spark Nlp written by Alex Thomas and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-25 with Computers categories.

If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

Natural Language Processing With Python

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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-01-16

Natural Language Processing With Python written by Cuantum Technologies LLC and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-16 with Computers categories.

Learn NLP with Python through practical exercises, advanced topics like transformers, and real-world projects such as chatbots and dashboards. A comprehensive guide for mastering NLP techniques. Key Features A comprehensive guide to processing, analyzing, and modeling human language with Python Real-world projects that reinforce NLP concepts, including chatbot design and sentiment analysis Foundational and advanced NLP techniques for practical applications in diverse domains Book DescriptionEmbark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques. Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery. The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.What you will learn Clean and preprocess text data using Python effectively Master tokenization techniques for words, sentences, and characters Build robust NLP pipelines with feature engineering methods Implement sentiment analysis with machine learning models Perform topic modeling using LDA, LSA, and other algorithms Develop chatbots and dashboards for real-world applications Who this book is for This book is ideal for students, researchers, and professionals in machine learning, data science, and artificial intelligence who want to master NLP. Beginners will benefit from the step-by-step introduction to text processing and feature engineering, while experienced practitioners can explore advanced topics like transformers and real-world projects. Basic knowledge of Python and familiarity with programming concepts are recommended to fully utilize the content. Enthusiasts with a passion for language technology will also find this guide valuable for building practical NLP applications.

Large Language Models For Sustainable Urban Development

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Author : Nitin Liladhar Rane
language : en
Publisher: Springer Nature
Release Date : 2025-07-01

Large Language Models For Sustainable Urban Development written by Nitin Liladhar Rane and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.

With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality. This book explores how innovative technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs) can transform urban development by offering intelligent, data-driven solutions. LLMs go beyond automation, acting as co-creators in addressing environmental sustainability, resource management, and equitable development. By analyzing regulations, best practices, and real-time data on phenomena such as air pollution and traffic, these models empower urban planners to design smarter, more sustainable cities while fostering collaboration across disciplines. Divided into five sections, the book explores the diverse applications of LLMs, from optimizing renewable energy systems and enhancing urban planning to revolutionizing construction practices and improving resource efficiency. It highlights case studies on integrating AI with smart infrastructure, ecological balance, and disaster resilience. While underscoring their transformative potential, the book also examines ethical considerations such as bias, privacy, and environmental impact. More than a collection of research, this work is a call to action for urban planners, data scientists, policymakers, and researchers to harness AI responsibly in building greener, more equitable urban futures.

Foundation Models For Natural Language Processing

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Author : Gerhard Paaß
language : en
Publisher: Springer Nature
Release Date : 2023-05-23

Foundation Models For Natural Language Processing written by Gerhard Paaß and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with Computers categories.

This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI.

Neural Information Processing

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Author : Biao Luo
language : en
Publisher: Springer Nature
Release Date : 2023-11-26

Neural Information Processing written by Biao Luo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-26 with Computers categories.

The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

The Making And Breaking Of Classification Models In Linguistics

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