This is one of the first books to provide a detailed and comprehensive account of recent empirical findings in the field of English as a lingua franca (ELF). Cogo and Dewey analyze and interpret their own large corpus of naturally occurring spoken interactions and focus on identifying innovative developments in the pragmatics and lexicogrammar of speakers engaged in ELF talk.
Cogo and Dewey's work makes a substantial contribution to the emerging field of empirical ELF studies. As well as this practical focus, this book looks at both pragmatic and lexicogrammatical issues and highlights their interrelationship. In showcasing the underlying processes involved in the emergence of innovative patterns of language use, this book will be of great interest to advanced students and academics working in applied linguistics, ELF, sociolinguistics, and corpus linguistics.
Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms. Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.Develop a naïve Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a “whom to follow” recommendation system from Twitter data
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 linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.Explore the machine learning landscape, particularly neural netsUse scikit-learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the TensorFlow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural netsApply practical code examples without acquiring excessive machine learning theory or algorithm details
But if you're serious about your profession, intuition isn't enough. Perl Best Practices author Damian Conway explains that rules, conventions, standards, and practices not only help programmers communicate and coordinate with one another, they also provide a reliable framework for thinking about problems, and a common language for expressing solutions. This is especially critical in Perl, because the language is designed to offer many ways to accomplish the same task, and consequently it supports many incompatible dialects.
With a good dose of Aussie humor, Dr. Conway (familiar to many in the Perl community) offers 256 guidelines on the art of coding to help you write better Perl code--in fact, the best Perl code you possibly can. The guidelines cover code layout, naming conventions, choice of data and control structures, program decomposition, interface design and implementation, modularity, object orientation, error handling, testing, and debugging.
They're designed to work together to produce code that is clear, robust, efficient, maintainable, and concise, but Dr. Conway doesn't pretend that this is the one true universal and unequivocal set of best practices. Instead, Perl Best Practices offers coherent and widely applicable suggestions based on real-world experience of how code is actually written, rather than on someone's ivory-tower theories on howsoftware ought to be created.
Most of all, Perl Best Practices offers guidelines that actually work, and that many developers around the world are already using. Much like Perl itself, these guidelines are about helping you to get your job done, without getting in the way.
Praise for Perl Best Practices from Perl community members:
"As a manager of a large Perl project, I'd ensure that every member of my team has a copy of Perl Best Practices on their desk, and use it as the basis for an in-house style guide."-- Randal Schwartz
"There are no more excuses for writing bad Perl programs. All levels of Perl programmer will be more productive after reading this book."-- Peter Scott
"Perl Best Practices will be the next big important book in the evolution of Perl. The ideas and practices Damian lays down will help bring Perl out from under the embarrassing heading of "scripting languages". Many of us have known Perl is a real programming language, worthy of all the tasks normally delegated to Java and C++. With Perl Best Practices, Damian shows specifically how and why, so everyone else can see, too."-- Andy Lester
"Damian's done what many thought impossible: show how to build large, maintainable Perl applications, while still letting Perl be the powerful, expressive language that programmers have loved for years."-- Bill Odom
"Finally, a means to bring lasting order to the process and product of real Perl development teams."-- Andrew Sundstrom"Perl Best Practices provides a valuable education in how to write robust, maintainable Perl, and is a definitive citation source when coaching other programmers."-- Bennett Todd"I've been teaching Perl for years, and find the same question keeps being asked: Where can I find a reference for writing reusable, maintainable Perl code? Finally I have a decent answer."-- Paul Fenwick"At last a well researched, well thought-out, comprehensive guide to Perl style. Instead of each of us developing our own, we can learn good practices from one of Perl's most prolific and experienced authors. I recommend this book to anyone who prefers getting on with the job rather than going back and fixing errors caused by syntax and poor style issues."-- Jacinta Richardson"If you care about programming in any language read this book. Even if you don't intend to follow all of the practices, thinking through your style will improve it."-- Steven Lembark"The Perl community's best author is back with another outstanding book. There has never been a comprehensive reference on high quality Perl coding and style until Perl Best Practices. This book fills a large gap in every Perl bookshelf."-- Uri Guttman
This second edition presents new developments and discoveries that have been made in the field. Parsing techniques have grown considerably in importance, both in computational linguistics where such parsers are the only option, and computer science, where advanced compilers often use general CF parsers. Parsing techniques provide a solid basis for compiler construction and contribute to all existing software: enabling Web browsers to analyze HTML pages and PostScript printers to analyze PostScript. Some of the more advanced techniques are used in code generation in compilers and in data compression.
In linguistics, the importance of formal grammars was recognized early on, but only recently have the corresponding parsing techniques been applied. Also their importance as general pattern recognizers is slowly being acknowledged. This text Parsing Techniques explores new developments, such as generalized deterministic parsing, linear-time substring parsing, parallel parsing, parsing as intersection, non-canonical methods, and non-Chomsky systems.
To provide readers with low-threshold access to the full field of parsing techniques, this new edition uses a two-tiered structure. The basic ideas behind the dozen or so existing parsing techniques are explained in an intuitive and narrative style, and problems are presented at the conclusion of each chapter, allowing the reader to step outside the bounds of the covered material and explore parsing techniques at various levels. The reader is also provided with an extensive annotated bibliography as well as hints and partial solutions to a number of problems. In the bibliography, hundreds of realizations and improvements of parsing techniques are explained in a much terser, yet still informal, style, improving its readability and usability.
The reader should have an understanding of algorithmic thinking, especially recursion; however, knowledge of any particular programming language is not required.
The first part provides an introduction to basic procedures for handling and operating with text strings. Then, it reviews major mathematical modeling approaches. Statistical and geometrical models are also described along with main dimensionality reduction methods. Finally, it presents some specific applications such as document clustering, classification, search and terminology extraction.
All descriptions presented are supported with practical examples that are fully reproducible. Further reading, as well as additional exercises and projects, are proposed at the end of each chapter for those readers interested in conducting further experimentation.
This comprehensive, reader-friendly volume offers readers a high-level orientation, discussing the foundations of the field and presenting both the classical work and the most recent results. It covers an extremely rich array of topics including not only syntax and semantics but also phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting.
As the first text of its kind, this innovative book will be a valuable tool and reference for those in information science (information retrieval and extraction, search engines) and in natural language technologies (speech recognition, optical character recognition, HCI). Exercises suitable for advanced readers are included as well as suggestions for further reading and an extensive bibliography.
"I'm pleased and impressed. The book is very readable, often entertaining---it tells what the issues are, what they are called, in what health they are, where more meat can be found. Given the enormous amount of material and concepts touched on, and the technical difficulties lying under the surface almost everywhere, the book betrays scholarship in a matter-of-fact way, making due impression on, but without clobbering, the reader. This is a book that invites READING THROUGH...".
Professor Tommaso Toffoli, Boston University, USA
"It is a remarkable achievement, essential reading for every linguist who aspires to be well informed about applications of mathematics in the language sciences."
Professor Geoffrey Pullum, University of Edinburgh, UK
"I really liked this book. First, it is written very well and secondly, the author has taken a rather non-standard but very attractive approach to mathematical linguistics. It is very refreshing."
Professor Aravind K. Joshi, University of Pennsylvania, USA
Perl has a strong history of automated tests. A very early release of Perl 1.0 included a comprehensive test suite, and it's only improved from there. Learning how Perl's test tools work and how to put them together to solve all sorts of previously intractable problems can make you a better programmer in general. Besides, it's easy to use the Perl tools described to handle all sorts of testing problems that you may encounter, even in other languages.
Like all titles in O'Reilly's Developer's Notebook series, this "all lab, no lecture" book skips the boring prose and focuses instead on a series of exercises that speak to you instead of at you.
Perl Testing: A Developer's Notebook will help you dive right in and:Write basic Perl tests with ease and interpret the resultsApply special techniques and modules to improve your testsBundle test suites along with projectsTest databases and their dataTest websites and web projectsUse the "Test Anything Protocol" which tests projects written in languages other than Perl
With today's increased workloads and short development cycles, unit tests are more vital to building robust, high-quality software than ever before. Once mastered, these lessons will help you ensure low-level code correctness, reduce software development cycle time, and ease maintenance burdens.
You don't have to be a die-hard free and open source software developer who lives, breathes, and dreams Perl to use this book. You just have to want to do your job a little bit better.
You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text.
By the end of this book, you will be confident about NLP and data science concepts and know how to apply them in your day-to-day work.
This book collects contributions from leading researchers in the area of natural language processing technology, describing their recent work and a range of new techniques and results. The book presents a state-of-the-art overview of current research in parsing tehcnologies with a focus on three important themes in the field today: dependency parsing, domain adaptation, and deep parsing.
This book is the fourth in a line of such collections, and its breadth over coverage should make it suitable both as an overview of the state of the field for graduate students, and as a reference for established researchers in Computational Linguistics, Artificial Intelligence, Computer Science, Language Engineering, Information Science, and Cognitive Science. It will also be of interest to designers, developers, and advanced users of nautral language processing systems, including applications such as spoken dialogue, text mining, multimodal human-computer interaction, and semantic web technology.
Computational Linguistics: Concepts, Methodologies, Tools, and Applications explores language by dissecting the phonemic aspects of various communication systems in order to identify similarities and pitfalls in the expression of meaning. With applications in a variety of areas, from psycholinguistics and cognitive science to computer science and artificial intelligence, this multivolume reference work will be of use to researchers, professionals, and educators on the cutting edge of language acquisition and communication science.
The Web is an exponentially increasing source of language and corpus linguistics data. From gigantic static information resources to user-generated Web 2.0 content, the breadth and depth of information available is breathtaking – and bewildering. This book explores the theory and practice of the "web as corpus†?. It looks at the most common tools and methods used and features a plethora of examples based on the author's own teaching experience. This book also bridges the gap between studies in computational linguistics, which emphasize technical aspects, and studies in corpus linguistics, which focus on the implications for language theory and use.
This book furnishes plenty of examples of idiomatic phrases and provides the foundation for how MT systems can process and translate idioms by means of simple linguistic resources.
· To challenge the student analytically, without requiring any explicit knowledge or experience in linguistics or computer science;
· To expose the student to the different kinds of reasoning required when encountering a new phenomenon in a language, both as a theoretical topic and as an applied problem;
· To foster the natural curiosity students have about the workings of their own language, as well as to introduce them to the beauty and structure of other languages;
· To learn about the models and techniques used by computers to understand human language.
Aside from being a fun intellectual challenge, the Olympiad mimics the skills used by researchers and scholars in the field of computational linguistics.
In an increasingly global economy where businesses operate across borders and languages, having a strong pool of computational linguists is a competitive advantage, and an important component to both security and growth in the 21st century.
This collection of problems is a wonderful general introduction to the field of linguistics through the analytic problem solving technique.
"A fantastic collection of problems for anyone who is curious about how human language works! These books take serious scientific questions and present them in a fun, accessible way. Readers exercise their logical thinking capabilities while learning about a wide range of human languages, linguistic phenomena, and computational models. " - Kevin Knight, USC Information Sciences Institute
This volume is a compilation of work by researchers, developers and practitioners of post-editing, presented at two recent events on post-editing: The first Workshop on Post-editing Technology and Practice, held in conjunction with the 10th Conference of the Association for Machine Translation in the Americas, held in San Diego, in 2012; and the International Workshop on Expertise in Translation and Post-editing Research and Application, held at the Copenhagen Business School, in 2012.
The Texture of Internet explores the latest linguistic issues regarding these language transformations focusing on texting, email writing, website texture, new digital genres such as blogs, and the potential applications of Internet to specific linguistic professional settings (e.g. translation, linguistic research or language teaching). This book will become a key reference for anyone interested in unveiling the intricacies of language use in our technological environment.
Santiago Posteguillo, María José Esteve, and Lluïsa Gea-Valor have compiled an excellent set of contributions from Spain, United Kingdom, and Hong Kong on the analysis of language use in Internet and Information and Communication Technologies. They all are researchers and teachers of Languages for Specific Purposes and Linguistics at Universitat Jaume I in Castelló, Spain. Their experience in Internet language analysis has produced a most valuable volume on the matter.
• Document structure analysis followed by OCR of Japanese, Tibetan and Indian printed scripts.
• Online and offline handwritten text recognition approaches;
• Japanese postal and Arabic check processing;
• Document image quality modelling, mathematical expression recognition, graphics recognition, document information retrieval, super resolution text, metadata extraction in digital library;
• Biometric and forensic aspects: individuality of handwriting detection;
• Web document analysis, text and hypertext mining and bank check data mining.
Containing chapters written by some of the most eminent researchers active in this field, this book can serve as a handbook for the research scholar as well as a supporting book for advanced graduate students interested in document processing or image analysis.
This is the first book to treat the topic of speech synthesis from the perspective of two different engineering approaches. The book will be of interest to researchers and students in phonetics and speech communication, in both academia and industry.
This case study contributes to the understanding of the speaker identification process in a situation where unknown speech samples are in different language/dialect than the recording of a suspect. The authors' data establishes that vowel quality, quantity, intonation and tone of a speaker as compared to Khariboli (standard Hindi) could be the potential features for identification of dialect accent.
The 17 full papers, 22 short papers, and 13 poster papers presented were carefully reviewed and selected from 83 submissions. The papers cover the following topics: theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP.
The book is divided into two sections, the first on monolingual corpora and the second addressing multilingual corpora. The range of languages covered includes English, French and German, but also Chinese and some of the less widely known and less widely explored central and eastern European language. The chapters discuss:
the relationship between methodology and theory
the importance of computers for linking textual segments, providing teaching tools, or translating texts
the significance of training corpora and human annotation
how corpus linguistic investigations can shed light on social and cultural aspects of language
Presenting fascinating research in the field, this book will be of interest to academics researching the applications of corpus linguistics in modern linguistic studies and the applications of corpus linguistics.