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101 NLP Exercises (using modern libraries)

I hope you found this useful. For more such posts, stay tuned to our page ! Desired Output: #> [(‘incredible’, 0.90), #> (‘awesome’, 0.82), #> (‘unbelievable’, 0.82), #> (‘fantastic’, 0.77), #> (‘phenomenal’, 0.76), #> (‘astounding’, 0.73), #> (‘wonderful’, 0.72), #> (‘unbelieveable’, 0.71), #> (‘remarkable’, 0.70), #> (‘marvelous’, 0.70)] Difficulty Level : L2 22. How to …

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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