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Pattern Recognition And Machine Learning | Foundations of Statistical Natural Language Processing | Natural Language Processing with Python | Hadoop | Practical Text Analytics | Representation And Inference For Natural Language | Statistical Methods for Speech Recognition | Modern Operating Systems | Artificial Intelligence
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
About: This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.
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