Natural Language Processing in Python: 10+ Packages You Can’t Miss (with Code)

Author(s): Davide Nardini

Originally published on Towards AI.

10+ Python packages for Natural Language Processing that you can’t miss, along with their corresponding code.
Foto di Max Duzij su Unsplash

Natural Language Processing is the field of Artificial Intelligence that involves text analysis. It combines statistics and mathematics with computational linguistics.

The main tasks of Natural Language Processing are:

Text ClassificationNamed Entity RecognitionPart of SpeechTopic ModelingText GenerationQuestion AnsweringKeyword ExtractionText Summarization… and so on

There are numerous Python projects available for handling Natural Language tasks.

In this article, I’ll introduce you to 10+ essential open-source Python packages for Natural Language Processing that you can’t miss.

Before starting, consider taking a look at my Medium profile where I cover topics on Data Science, Machine Learning, and Python!

NLTK stands for Natural Language Toolkit, comprising Python modules, datasets, corpora, and tutorials designed for Natural Language Processing (NLP). It stands as one of the most revered and recognized packages in Python, demonstrated by its impressive 12.6k stars on GitHub.

NLTK serves various purposes including text preprocessing, translation, and NLP tasks such as text classification, utilizing a multitude of implemented algorithms.

Allow me to provide an example from the official documentation:

import nltk sentence = """At eight o'clock on Thursday morning… Arthur didn't feel very good."""

Word Tokenization:

tokens = nltk.word_tokenize(sentence)print(tokens)'''['At', 'eight', "o'clock", 'on', 'Thursday', 'morning','Arthur', 'did', "n't", 'feel', 'very', 'good', '.']'''

Part of Speech:

tagged = nltk.pos_tag(tokens)print(tagged)'''[('At', 'IN'), ('eight', 'CD'), ("o'clock", 'JJ'),… Read the full blog for free on Medium.

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Published via Towards AI