Python For Linguists
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Python For Linguists
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Author : Michael Hammond
language : en
Publisher: Cambridge University Press
Release Date : 2020-05-07
Python For Linguists written by Michael Hammond 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 2020-05-07 with Computers categories.
An introduction to Python programming for linguists. Examples of code specifically designed for language analysis are featured throughout.
An Introduction To Python
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Author : Guido Van Rossum
language : en
Publisher: Network Theory.
Release Date : 2011-03
An Introduction To Python written by Guido Van Rossum and has been published by Network Theory. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03 with Python (Computer program language) categories.
"This manual is part of the official reference documentation for Python, an object-oriented programming language created by Guido van Rossum. Python is free software. The term “free software” refers to your freedom to run, copy, distribute, study, change and improve the software. With Python you have all these freedoms. You can support free software by becoming an associate member of the Free Software Foundation. The Free Software Foundation is a tax-exempt charity dedicated to promoting the right to use, study, copy, modify, and redistribute computer programs. It also helps to spread awareness of the ethical and political issues of freedom in the use of software. For more information visit the website www.fsf.org. The development of Python itself is supported by the Python Software Foundation. Companies using Python can invest in the language by becoming sponsoring members of this group. Donations can also be made online through the Python website. Further information is available at http://www.python.org/psf/."--Page 1.
Statistics For Linguists An Introduction Using R
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Author : Bodo Winter
language : en
Publisher: Routledge
Release Date : 2019-10-30
Statistics For Linguists An Introduction Using R written by Bodo Winter and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-30 with Education categories.
Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models for linguistics. The book covers simple uses of linear models through generalized models to more advanced approaches, maintaining its focus on conceptual issues and avoiding excessive mathematical details. It contains many applied examples using the R statistical programming environment. Written in an accessible tone and style, this text is the ideal main resource for graduate and advanced undergraduate students of Linguistics statistics courses as well as those in other fields, including Psychology, Cognitive Science, and Data Science.
Applied Text Analysis With Python
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Author : Benjamin Bengfort
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-06-11
Applied Text Analysis With Python written by Benjamin Bengfort 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 2018-06-11 with Computers categories.
From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
Analyzing Linguistic Data
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Author : R. H. Baayen
language : en
Publisher: Cambridge University Press
Release Date : 2008-03-06
Analyzing Linguistic Data written by R. H. Baayen 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 2008-03-06 with Language Arts & Disciplines categories.
Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.
Hands On Natural Language Processing With Python
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Author : Rajesh Arumugam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-18
Hands On Natural Language Processing With Python written by Rajesh Arumugam 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 2018-07-18 with Computers categories.
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Quantitative Research In Linguistics
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Author : Sebastian M. Rasinger
language : en
Publisher: A&C Black
Release Date : 2013-12-05
Quantitative Research In Linguistics written by Sebastian M. Rasinger and has been published by A&C Black this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-05 with Language Arts & Disciplines categories.
Presents a comprehensive introduction to analysing quantitative linguistic data. Starting with an definition of quantitative data, and how it differs from qualitative data, Seb Rasinger examines what the student linguist is trying to find out through analysing data, and how quantitative techniques can help arrive at meaningful and accurate conclusions. This expanded, 2nd edition now also includes a discussion of Analysis of Variance (ANOVA) and MANOVA, and provides a brief introduction to statistical meta-analysis. A companion website allows readers to download crib sheets and Excel templates for the main statistical tools. The book introduces: -using statistics -variables -reliability of data -describing data -analysing data -testing hypotheses -dealing with problematic data. Each chapter includes graphs and figures explaining theory through worked examples, chapter summaries, and exercises to aid student understanding. An appendix containing a summary of statistical formulae, excel commands and statistical tables is included and is an invaluable resource. Presenting a down-to-earth and readable introduction to quantitative research, this book is a useful how-to guide for students encountering quantitative data for the first time, or for postgraduates embarking on linguistic research projects.
Combinatory Linguistics
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Author : Cem Bozsahin
language : en
Publisher: Walter de Gruyter
Release Date : 2012-12-06
Combinatory Linguistics written by Cem Bozsahin and has been published by Walter de Gruyter this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Language Arts & Disciplines categories.
The book examines to what extent the mediating relation between constituents and their semantics can arise from combinatory knowledge of words. It traces the roots of Combinatory Categorial Grammar, and uses the theory to promote a Humean question in linguistics and cognitive science: Why do we see limited constituency and dependency in natural languages, despite their diversity and potential infinity? A potential answer is that constituents and dependencies might have arisen from a single resource: adjacency. The combinatory formulation of adjacency constrains possible grammars.
Computational Semantics With Functional Programming
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Author : Jan van Eijck
language : en
Publisher: Cambridge University Press
Release Date : 2010-09-23
Computational Semantics With Functional Programming written by Jan van Eijck 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 2010-09-23 with Language Arts & Disciplines categories.
Computational semantics is the art and science of computing meaning in natural language. The meaning of a sentence is derived from the meanings of the individual words in it, and this process can be made so precise that it can be implemented on a computer. Designed for students of linguistics, computer science, logic and philosophy, this comprehensive text shows how to compute meaning using the functional programming language Haskell. It deals with both denotational meaning (where meaning comes from knowing the conditions of truth in situations), and operational meaning (where meaning is an instruction for performing cognitive action). Including a discussion of recent developments in logic, it will be invaluable to linguistics students wanting to apply logic to their studies, logic students wishing to learn how their subject can be applied to linguistics, and functional programmers interested in natural language processing as a new application area.
The Cambridge Handbook Of English Corpus Linguistics
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Author : Douglas Biber
language : en
Publisher: Cambridge University Press
Release Date : 2015-06-25
The Cambridge Handbook Of English Corpus Linguistics written by Douglas Biber 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 2015-06-25 with Language Arts & Disciplines categories.
The Cambridge Handbook of English Corpus Linguistics (CHECL) surveys the breadth of corpus-based linguistic research on English, including chapters on collocations, phraseology, grammatical variation, historical change, and the description of registers and dialects. The most innovative aspects of the CHECL are its emphasis on critical discussion, its explicit evaluation of the state of the art in each sub-discipline, and the inclusion of empirical case studies. While each chapter includes a broad survey of previous research, the primary focus is on a detailed description of the most important corpus-based studies in this area, with discussion of what those studies found, and why they are important. Each chapter also includes a critical discussion of the corpus-based methods employed for research in this area, as well as an explicit summary of new findings and discoveries.