Lemmatization

Complete Guide to Natural Language Processing (NLP) – with Practical Examples

Natural language processing (NLP) is the technique by which computers understand the human language. NLP allows you to perform a wide range of tasks such as classification, summarization, text-generation, translation and more. NLP has advanced so much in recent times that AI can write its own movie scripts, create poetry, summarize text and answer questions …

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spaCy Tutorial – Complete Writeup

spaCy is an advanced modern library for Natural Language Processing developed by Matthew Honnibal and Ines Montani. This tutorial is a complete guide to learn how to use spaCy for various tasks. Overview 1. Introduction The Doc object 2. Tokenization with spaCy 3. Text-Preprocessing with spaCy 4. Lemmatization 5. Strings to Hashes 6. Lexical attributes …

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Lemmatization Approaches with Examples in Python

Lemmatization is the process of converting a word to its base form. The difference between stemming and lemmatization is, lemmatization considers the context and converts the word to its meaningful base form, whereas stemming just removes the last few characters, often leading to incorrect meanings and spelling errors. Comparing Lemmatization Approaches in Python. Photo by …

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Machine Learning A-Z™: Hands-On Python & R In Data Science

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science