preface chapter 1:introduction understan natural language processing understan basic applications understan advanced applications advantages of togetherness-n lp and python environment setup for nltk ti for readers summary chapter 2:practical understan of a corpus and datase what is a corpus? why do we need a corpus? understan corpus analysis exercise understan types of data attributes categorical or qualitative data attributes numeric or quantitative data attributes exploring different file formats for corpora resources for accessing free corpora preparing a dataset for nlp applications selecting data preprocessing the dataset formatting cleaning sampling transforming data web scraping summary chapter 3:understan the structure of a sentences understan ponents of nlp natural language understan natural language generation differences between nlu and nlg branches nf nlp defining context-free grammar exercise morphological analysis what is morphology? what are morphemes? what is a stem? what is morphological analysis? what is a word? classification of morphemes free morphemes bound morphemes derivational morphemes inflectional morphemes what is the difference between a stem and a root? exercise lecal analysis ……
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