He was involved in the establishment of Edinburgh's Language Technology Group in 1993, and has been closely associated with it ever since. After some years working at the Universities of Sussex and Newcastle upon Tyne, Ewan took up a teaching position at Edinburgh. He completed a PhD on formal semantics at the University of Cambridge in 1978. Ewan Klein is Professor of Language Technology in the School of Informatics at the University of Edinburgh. Steven is Vice President of the Association for Computational Linguistics. Back at Melbourne University, he established a language technology research group and has taught at all levels of the undergraduate computer science curriculum. More recently, he spent several years as Associate Director of the Linguistic Data Consortium where he led an R&D team to create models and tools for large databases of annotated text. He later moved to Cameroon to conduct linguistic fieldwork on the Grassfields Bantu languages under the auspices of the Summer Institute of Linguistics. After completing his undergraduate training in computer science and mathematics at the University of Melbourne, Steven went to the University of Edinburgh to study computational linguistics, and completed his PhD in 1990 under the supervision of Ewan Klein. Steven Bird is Associate Professor in the Department of Computer Science and Software Engineering at the University of Melbourne, and Senior Research Associate in the Linguistic Data Consortium at the University of Pennsylvania. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages - or if you're simply curious to have a programmer's perspective on how human language works - you'll find Natural Language Processing with Python both fascinating and immensely useful. This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence.Access popular linguistic databases, including WordNet and treebanks.Analyze linguistic structure in text, including parsing and semantic analysis.Extract information from unstructured text, either to guess the topic or identify "named entities".Packed with examples and exercises, Natural Language Processing with Python will help you: 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. With it, you'll learn how to write Python programs that work with large collections of unstructured text. 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.
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