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If you have spent, or plan to spend, some time exploring the world of natural language understanding, you will understand better than most how difficult it is to proceed. If you are looking for a shortcut around the learning curve, perhaps by reading about how others tackled this complex area of study then the ebook below might be just what you are looking for. Named one of Machine Learning's most read-worthy publications in 2013, James Allen's text is clearly written with the novice in mind but still has enough depth to appeal to those more familiar with machine learning. The book offers a step by step explanation of how machine learners can start by building an ML system that can find information on Wikipedia articles and web pages. These intro systems might not be able to answer all your knowledge questions, but will provide grounding on what is involved in NLP and how it can be used to further the field of machine learning. The text also provides a closer look at what makes up a larger system for understanding natural language by using the powerful programming tool Python. Allen takes the reader through installing Python and getting started with some of its popular applications. Among these are NLTK (the Natural Language Toolkit), which contains libraries for retrieving data from sources such as Wikipedia or WordNet, as well as tools that can generate sentences based on concepts. Allen uses the NLTK library to demonstrate his points about performing sentiment analysis, a process of identifying opinions expressed in a text similar to determining if a review is positive or negative. Sentiment analysis is a common problem in NLP and, as it turns out, a much simpler one than parsing sentences to interpret meaning. Sentiment analysis could be used, for example, by companies that want to improve their customer service. The company would collect data from social media sites such as Twitter or Facebook to find remarks that are both relevant and negative (so they can learn what their customers aren't happy with). This information could then be used to create targeted advertising campaigns designed to correct the issues raised by their customers. The book is dedicated to Allen's wife, Mary E. Allen, who died of cancer in 2000. "McGraw-Hill Professional" named the book one of its most read-worthy publications in 2013. "Analysis of Sentiment Using Opinion Mining on Twitter", Computer Science Department, University of North Carolina at Chapel Hill , June 2, 2010 - June 9, 2010. "Machine Learning", James R. Allen, Dec. 2013. Category:Articles written by James Allen "Natural Language Application Frameworks - A Survey", Ghada Hatem, Farid Z. Sharafat, 2014. "Natural Language Processing with Python", Andreas Müller, Steven Bird, 2005. Category:Textbooks by James Allen "Natural Language Understanding - The Linguistic Basis of Computational Linguistics", James Allen - Free ebook download as PDF File (.pdf), Text File (.txt) or read book online for free. cfa1e77820
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