Foundations of Statistical Natural Language Processing Christopher D. Manning, Hinrich Schuetze
Publisher: MIT

O Pattern Recognition and Machine Learning by Bishop and Pattern Classification by Duda and Hart. First, I thought "Foundations of Statistical Natural Language Processing" did a remarkable job talking about big data for NLP. Ɯ书具有“覆盖全面、注重实用、强调评测、语料为本”四大特色。在本书的配套网站上，还提供了相关的资源和工具，便于读者在实践中进一步提高。 2、 Foundations of Statistical Natural Language Processing a) 作者: Christopher D. Semantics Oriented Natural Language Processing: Mathematical Models. My favorite tech book is Foundations of Statistical Natural Language Processing. Related Books: Natural Language Processing. While NLP is only one part of AI, it still may be of interest. Foundations of Statistical Natural Language Processing. Yet Shannon (1948) mentions at least twice that base 2 is to be used when measuring bits. The book contains all the theory and algorithms. My favorite literary book is The History of Love by Nicole Krauss. We used the open source NLTK version 2.0 with Python version 2.6 (Python Software Foundation, Wolfeboro Falls, NH, USA) to analyze preprocessed text. A short trip to the library and also a look into the cited work of the papers made me find the book Foundations of statistical natural language processing by Christopher D. Bayesian Reasoning and Machine Learning by David Barber [website]; Information Theory, Inference, and Learning Algorithms by David J.C. "Foundations of Statistical Natural Language Processing" 2.21 says "using any other base yields only a linear scaling of results". This has been a Bible for me in terms of statistical NLP.