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Ido Greenberg2017NLTK Book Summary Natural Language ToolKit most popular NLP toolkit of Python. Source: http://www.nltk.org/book/ Summarized by Ido Greenberg, 2017Contents Preface .............................................................................................................................................
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Identify the specific use case for natural language processing
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Collect and preprocess the necessary text data
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Choose an appropriate NLP tool or library for the task
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Businesses looking to automate customer support through chatbots
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Natural language processing (NLP) is a field of artificial intelligence that enables computers to understand, interpret, and generate human language.
Researchers, developers, and organizations that implement NLP systems may need to file documentation or reports regarding their applications depending on legal and regulatory requirements.
Filling out natural language processing submissions typically involves providing detailed information on the algorithms used, data sources, methodologies, and potential ethical considerations.
The purpose of NLP is to facilitate interaction between computers and humans using natural language, enabling applications such as speech recognition, sentiment analysis, and translation.
Reports should include information about the algorithms applied, training data used, performance metrics, and compliance with ethical standards.
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2017 2006 nltk greenberg parsing classifier syntactic nlp pp chunker regex lexical nn iteratively nps xml segmentation parsed unigram cfg taggers parser bayes wrt interpretable wordnet slashnp jj treebank classifiers tokenization morphological lemmatizati

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