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spacy library in python
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Download this code from https://codegive.com • spaCy is a popular open-source library for Natural Language Processing (NLP) in Python. It provides pre-trained models and tools for various NLP tasks, making it a powerful and efficient choice for text processing. In this tutorial, we'll explore the basic features of spaCy and walk through practical examples. • To install spaCy, use the following pip command: • Additionally, you'll need to download a language model. For English, the most common model is en_core_web_sm. You can download it using: • Let's start with a simple example to demonstrate how to use spaCy for tokenization, part-of-speech tagging, and named entity recognition. • spaCy can also lemmatize words, providing their base or dictionary form. • Dependency parsing allows you to analyze the grammatical structure of a sentence. • The Matcher class in spaCy allows you to define rules to find sequences of tokens based on their attributes. • spaCy also supports text classification using pre-trained models. Here's a simple example: • This tutorial covers the basic and advanced features of spaCy, a versatile library for natural language processing in Python. spaCy simplifies complex NLP tasks, making it a valuable tool for researchers, developers, and data scientists working with text data. Explore the official spaCy documentation for more details and customization options: spaCy Documentation. • ChatGPT
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