This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.Packed with examples and exercises, Natural Language Processi... [Read More]
Graphics in this book are printed in black and white.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’l... [Read More]
For undergraduate or advanced undergraduate courses in Classical Natural Language Processing, Statistical Natural Language Processing, Speech Recognition, Computational Linguistics, and Human Language Processing. An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this text takes an empirical approach to the subject, based on apply... [Read More]
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, i... [Read More]
Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic... [Read More]
This book explains how to build Natural Language Generation (NLG) systems--computer software systems that automatically generate understandable texts in English or other human languages. NLG systems use knowledge about language and the application domain to automatically produce documents, reports, explanations, help messages, and other kinds of texts. The book covers the algorithms and representations needed to perform the core tasks of document planning, microplanning, and surface realization, using a case study to show how these components fit together. It is essential reading for researche... [Read More]
Key FeaturesSecond edition of the bestselling book on Machine LearningA practical approach to key frameworks in data science, machine learning, and deep learningUse the most powerful Python libraries to implement machine learning and deep learningGet to know the best practices to improve and optimize your machine learning systems and algorithmsBook DescriptionMachine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Rasc... [Read More]
This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forward Includes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has produced Presents the major developments in an accessible way, explaining the close connection between scientific understanding of the computational properties of natur... [Read More]
This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-p... [Read More]
Our love affair with the digital interface is out of control. We’ve embraced it in the boardroom, the bedroom, and the bathroom. Screens have taken over our lives. Most people spend over eight hours a day staring at a screen, and some “technological innovators” are hoping to grab even more of your eyeball time. You have screens in your pocket, in your car, on your appliances, and maybe even on your face. Average smartphone users check their phones 150 times a day, responding to the addictive buzz of Facebook or emails or Twitter. Are you sick? There’s an app for that! Need ... [Read More]
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple l... [Read More]
“You either love Andrea Camilleri or you haven’t read him yet. Each novel in this wholly addictive, entirely magical series, set in Sicily and starring a detective unlike any other in crime fiction, blasts the brain like a shot of pure oxygen. Aglow with local color, packed with flint-dry wit, as fresh and clean as Mediterranean seafood — altogether transporting. Long live Camilleri, and long live Montalbano.” A.J. Finn, #1 New York Times bestselling author of The Woman in the WindowA hail of bullets interrupts a period of dead calm. An elderly brother and sister open fire on the pl... [Read More]
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical... [Read More]
A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples.The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, acro... [Read More]
Do you dream about learning a second language?What if I told you that there was a fast and natural way for you to learn Spanish?How? With this amazingly easy to follow audiobook!This audiobook was truly
This book is a compilation of texts, exercises, and a vast amount resources as used in the best universities to teach Portuguese to Foreigners. It includes the most effective methods to learn the Portuguese Language,
Studienarbeit aus dem Jahr 2006 im Fachbereich Sprachwissenschaft / Sprachforschung (fachübergreifend), Note: 1,3, Universität Hildesheim (Stiftung), 3 Quellen im Literaturverzeichnis, Sprache: Deutsch, Abstract: Das Forschungsgebiet Natural Language Processing ist eng mit der Erforschung der menschlichen
Originally published in 1992, when connectionist natural language processing (CNLP) was a new and burgeoning research area, this book represented a timely assessment of the state of the art in the field. It includes contributions
Many NLP tasks have at their core a subtask of extracting the dependencies-who did what to whom-from natural language sentences. This task can be understood as the inverse of the problem solved in different ways
This book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and
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