Natural Language Processing with Python and spaCy
A Practical Introduction
Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going.
You'll also learn how to: Work with word vectors to mathematically find words with similar meanings; Identify patterns within data using spaCy's built-in displaCy visualizer; Automatically extract keywords from user input and store them in a relational database; Deploy a chatbot app to interact with users over the internet.
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