Modelling With Words

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Modelling with Words

Author : Jonathan Lawry
Publisher : Springer Science & Business Media
ISBN 13 : 3540204873
Total Pages : 241 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Modelling with Words by : Jonathan Lawry

Download or read book Modelling with Words written by Jonathan Lawry and published by Springer Science & Business Media. This book was released on 2003-11-10 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Text Mining with R

Author : Julia Silge
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491981628
Total Pages : 193 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Text Mining with R by : Julia Silge

Download or read book Text Mining with R written by Julia Silge and published by "O'Reilly Media, Inc.". This book was released on 2017-06-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.

Deep Learning for Natural Language Processing

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 413 pages
Book Rating : 4./5 ( download)

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Book Synopsis Deep Learning for Natural Language Processing by : Jason Brownlee

Download or read book Deep Learning for Natural Language Processing written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2017-11-21 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods are achieving state-of-the-art results on challenging machine learning problems such as describing photos and translating text from one language to another. In this new laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about natural language processing. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what natural language processing is, the promise of deep learning in the field, how to clean and prepare text data for modeling, and how to develop deep learning models for your own natural language processing projects.

Neural Networks for Natural Language Processing

Author : S., Sumathi
Publisher : IGI Global
ISBN 13 : 1799811611
Total Pages : 227 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Neural Networks for Natural Language Processing by : S., Sumathi

Download or read book Neural Networks for Natural Language Processing written by S., Sumathi and published by IGI Global. This book was released on 2019-11-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

Modelling with Words

Author : Jonathan Lawry
Publisher : Springer
ISBN 13 : 3540399062
Total Pages : 241 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Modelling with Words by : Jonathan Lawry

Download or read book Modelling with Words written by Jonathan Lawry and published by Springer. This book was released on 2003-10-28 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Modeling Words in the Mind

Author : Constantine Lignos
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.:/5 (871 download)

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Book Synopsis Modeling Words in the Mind by : Constantine Lignos

Download or read book Modeling Words in the Mind written by Constantine Lignos and published by . This book was released on 2013 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence

Author : Gogate, Lakshmi
Publisher : IGI Global
ISBN 13 : 1466629746
Total Pages : 451 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence by : Gogate, Lakshmi

Download or read book Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence written by Gogate, Lakshmi and published by IGI Global. This book was released on 2013-02-28 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.

Teaching Beginning Reading and Writing with the Picture Word Inductive Model

Author : Emily Calhoun
Publisher : ASCD
ISBN 13 : 0871203375
Total Pages : 134 pages
Book Rating : 4.8/5 (712 download)

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Book Synopsis Teaching Beginning Reading and Writing with the Picture Word Inductive Model by : Emily Calhoun

Download or read book Teaching Beginning Reading and Writing with the Picture Word Inductive Model written by Emily Calhoun and published by ASCD. This book was released on 1999 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this practical guide to teaching beginning language learners of all ages, Calhoun encourages us to begin where the learners begin--with their developed listening and speaking vocabularies and other accumulated knowledge about the world. Engage students in shaking words out of a picture--words from their speaking vocabularies--to begin the process of building their reading and writing skills. Use the picture word inductive model (PWIM) to teach several skills simultaneously, beginning with the mechanics of forming letters to hearing and identifying the phonetic components of language, to classifying words and sentences, through forming paragraphs and stories based on observation. Built into the PWIM is the structure required to assess the needs and understandings of your students immediately, adjust the lesson in response, and to use explicit instruction and inductive activities. Individual, small-group, and large-group activities are inherent to the model and flow naturally as the teacher arranges instruction according to the 10 steps of the PWIM. Students and teachers move through the model and work on developing skills and abilities in reading, writing, listening, and comprehension as tools for thinking, learning, and sharing ideas.

Mastering Machine Learning with Spark 2.x

Author : Alex Tellez
Publisher : Packt Publishing Ltd
ISBN 13 : 1785282417
Total Pages : 334 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Mastering Machine Learning with Spark 2.x by : Alex Tellez

Download or read book Mastering Machine Learning with Spark 2.x written by Alex Tellez and published by Packt Publishing Ltd. This book was released on 2017-08-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book Process and analyze big data in a distributed and scalable way Write sophisticated Spark pipelines that incorporate elaborate extraction Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn Use Spark streams to cluster tweets online Run the PageRank algorithm to compute user influence Perform complex manipulation of DataFrames using Spark Define Spark pipelines to compose individual data transformations Utilize generated models for off-line/on-line prediction Transfer the learning from an ensemble to a simpler Neural Network Understand basic graph properties and important graph operations Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

The Naïve Bayes Model for Unsupervised Word Sense Disambiguation

Author : Florentina T. Hristea
Publisher : Springer Science & Business Media
ISBN 13 : 3642336930
Total Pages : 79 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis The Naïve Bayes Model for Unsupervised Word Sense Disambiguation by : Florentina T. Hristea

Download or read book The Naïve Bayes Model for Unsupervised Word Sense Disambiguation written by Florentina T. Hristea and published by Springer Science & Business Media. This book was released on 2012-11-07 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances (from 2008 to 2012) concerning use of the Naïve Bayes model in unsupervised word sense disambiguation (WSD). While WSD, in general, has a number of important applications in various fields of artificial intelligence (information retrieval, text processing, machine translation, message understanding, man-machine communication etc.), unsupervised WSD is considered important because it is language-independent and does not require previously annotated corpora. The Naïve Bayes model has been widely used in supervised WSD, but its use in unsupervised WSD has led to more modest disambiguation results and has been less frequent. It seems that the potential of this statistical model with respect to unsupervised WSD continues to remain insufficiently explored. The present book contends that the Naïve Bayes model needs to be fed knowledge in order to perform well as a clustering technique for unsupervised WSD and examines three entirely different sources of such knowledge for feature selection: WordNet, dependency relations and web N-grams. WSD with an underlying Naïve Bayes model is ultimately positioned on the border between unsupervised and knowledge-based techniques. The benefits of feeding knowledge (of various natures) to a knowledge-lean algorithm for unsupervised WSD that uses the Naïve Bayes model as clustering technique are clearly highlighted. The discussion shows that the Naïve Bayes model still holds promise for the open problem of unsupervised WSD.

DNA, Words and Models

Author : Stéphane Robin
Publisher : Cambridge University Press
ISBN 13 : 9780521847292
Total Pages : 168 pages
Book Rating : 4.8/5 (472 download)

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Book Synopsis DNA, Words and Models by : Stéphane Robin

Download or read book DNA, Words and Models written by Stéphane Robin and published by Cambridge University Press. This book was released on 2005-10-13 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description

Where Words Get their Meaning

Author : Marianna Bolognesi
Publisher : John Benjamins Publishing Company
ISBN 13 : 9027260427
Total Pages : 222 pages
Book Rating : 4.0/5 (272 download)

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Book Synopsis Where Words Get their Meaning by : Marianna Bolognesi

Download or read book Where Words Get their Meaning written by Marianna Bolognesi and published by John Benjamins Publishing Company. This book was released on 2020-11-15 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Words are not just labels for conceptual categories. Words construct conceptual categories, frame situations and influence behavior. Where do they get their meaning? This book describes how words acquire their meaning. The author argues that mechanisms based on associations, pattern detection, and feature matching processes explain how words acquire their meaning from experience and from language alike. Such mechanisms are summarized by the distributional hypothesis, a computational theory of meaning originally applied to word occurrences only, and hereby extended to extra-linguistic contexts. By arguing in favor of the cognitive foundations of the distributional hypothesis, which suggests that words that appear in similar contexts have similar meaning, this book offers a theoretical account for word meaning construction and extension in first and second language that bridges empirical findings from cognitive and computer sciences. Plain language and illustrations accompany the text, making this book accessible to a multidisciplinary academic audience.

Visual Word Recognition

Author : James S. Adelman
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (128 download)

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Book Synopsis Visual Word Recognition by : James S. Adelman

Download or read book Visual Word Recognition written by James S. Adelman and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Supervised Machine Learning for Text Analysis in R

Author : Emil Hvitfeldt
Publisher : CRC Press
ISBN 13 : 1000461971
Total Pages : 402 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Supervised Machine Learning for Text Analysis in R by : Emil Hvitfeldt

Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.

The Structure of the Lexicon

Author : Jürgen Handke
Publisher : Walter de Gruyter
ISBN 13 : 3110907860
Total Pages : 400 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis The Structure of the Lexicon by : Jürgen Handke

Download or read book The Structure of the Lexicon written by Jürgen Handke and published by Walter de Gruyter. This book was released on 2012-08-06 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:

R for Data Science

Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

The Child and Childhood in Folk Thought

Author : Alexander Francis Chamberlain
Publisher : IndyPublish.com
ISBN 13 :
Total Pages : 484 pages
Book Rating : 4.A/5 ( download)

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Book Synopsis The Child and Childhood in Folk Thought by : Alexander Francis Chamberlain

Download or read book The Child and Childhood in Folk Thought written by Alexander Francis Chamberlain and published by IndyPublish.com. This book was released on 1896 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1896. The Child in Primitive Culture. Contents: Child-Study; The Child's Tribute to the Mother; The Child's Tribute to the Father; The Name Child; The Child in the Primitive Laboratory; The Bright Side of Child-Life: Parental Affection; Childhood the Golden Age; Children's Food; Children's Souls; Children's Flowers, Plants, and Trees; Children's Animals, Birds, etc.; Child-Life and Education in General; The Child as Member and Builder of Society; The Child as Linguist; The Child as Actor and Inventor; The Child as Poet and Musician; The Child as Teacher and Wiseacre; The Child as Judge; The Child as Oracle-Keeper and Oracle-Interpreter; The Child as Weather-Maker; The Child as Healer and Physician; The Child as Shaman and Priest; The Child as Hero, Adventurer, etc.; The Child as Fetich and Divinity; The Child as God: The Christ-Child; Proverbs, Sayings, etc., about Parents, Father and Mother; Proverbs, Sayings, etc., about the Child, Mankind, Genius; Proverbs, Sayings, etc., about Mother and Child; Proverbs, Sayings, etc., about Father and Child; Proverbs, Sayings, etc., about Childhood, Youth, and Age; and Proverbs, Sayings, etc., about the Child and Childhood.