Which are the top 5 Python Libraries in the field of NLP?

An NLP library should have an intuitive API and be capable of quickly applying the most up-to-date algorithms and models.

  • NLTK - The NLTK Python framework is widely used to create applications that interact with human language data. It gives you a hands-on introduction to programming in language processing.
  • Genism - According to the creators, Gensim is one of the most popular Python NLP Libraries for “topic modeling, document indexing, and similarity retrieval with large corpora.” In terms of corpus size, Gensim’s algorithms are memory-independent, therefore it can handle input larger than RAM.
  • Core NLP - Stanford CoreNLP is a set of tools for analyzing human language. Its purpose is to make applying linguistic analysis tools on text as simple and efficient as possible. CoreNLP can extract all types of text characteristics with just a few lines of code.
  • SpaCy - It is an open-source Natural Language Processing toolbox written in Python. It was created with business users in mind, allowing you to design programs that process and analyze massive quantities of text.
  • TextBlob - TextBlob is a Python 2 and Python 3 text processing module. It focuses on providing user-friendly interfaces for common text-processing tasks.