7 Best Python NLP Libraries for your Next Project

7 Best NLP libraries for Python Projects to build efficient NLP applications. | ProjectPro

7 Best Python NLP Libraries for your Next Project
 |  BY Manika

Python is one of the most popular programming languages for building NLP projects. If you are interested in learning the reasons behind this popularity of Python among masses for creating NLP projects solutions, read this article till the end. It discusses the best Python NLP libraries in Python and a project idea to help you build an in-depth understanding of these libraries usage.


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7 Best Python NLP Libraries for your Next Project

Here is a list of five amazing libraries in Python that are best suited for NLP applications.

  1. SpaCy

SpaCy is an open-source library in Python that is used for completing Natural Language Processing (NLP) tasks. As per its official website, SpaCy supports about 72+ languages and can handle large textual datasets fluently. SpaCy comes with two powerful functionalities, namely, Parts-of-speech (POS) Tagging and Named-Entity Recognition Tagging. It is well-suited for solving industry-level problems. It is widely used for text preprocessing and computational linguistics purposes. It has state-of-the-art speed and results in rigorously evaluated accuracy.

Project Idea: NLP Project to Build a Resume Parser in Python using Spacy 

  1. Gensim

Gensim is the Python library used for vectorizing textual data before passing the data at the input of a machine learning model. It is useful in completing tasks like Topic Modeling and semantic modeling. The library supports scalable solutions by utilizing Python’s in-built iterators and generators for streamed data processing. This means the dataset is never loaded in the system’s RAM. Gensim is thus memory-independent and provides multicore implementations of latent Dirichlet allocation, latent semantic analysis, hierarchical Dirichlet process (HDP), random projections, and word2vec deep learning model.

Project Idea: Word2Vec and FastText Word Embedding with Gensim in Python 

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  1. NLTK

NLTK stands for Natural Language ToolKit. It is one of the leading libraries for working with textual data. Along with an active discussion forum, this library has methods that assist in various tasks such as classification, stemming, parsing, tagging, tokenization, semantic reasoning, and wrappers for other NLP libraries. It supports a user-friendly interface for about 50 corpora and lexical resources. 

Project Idea: Natural language processing Chatbot application using NLTK for text classification

  1. Pattern

The pattern is another famous library used for implementing NLP techniques in Python. It can be used for web mining, network analysis, and text processing. The Pattern library comes with an interesting set of tools for NLP (POS Tagging, sentiment analysis, n-gram search, and WordNet), Data mining (HTML DOM parser, Twitter, Google, WIkipedia API, and a web crawler), Machine Learning (clustering, Support Vector Machine, vector space model), and analysis of network with the help of visualization and graph centrality. 

Project Idea: Python for NLP: Using Pattern Library | Kaggle  

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  1. CoreNLP

This Python library consists of a variety of human language innovation tools. It aims at making the application of semantic analysis tools on textual data easy and highly efficient. Core NLP supports quick extraction of properties from textual data like named-entity-recognition, POS Tagging, etc., in a few lines of code. One necessary requirement for utilizing this library is that your system must have Java installed in it as its code is written in Java. You can easily use it with Python as CoreNLP offers interfaces for commonly used programming languages. CoreNLP can be used for four more languages besides English: Chinese, Arabic, French, Spanish, and German.

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  1. TextBlob

TextBlob is another open-source library in Python (2 & 3) backed by the NLTK library. It consists of various methods for supporting various text-processing tasks through simple interfaces. It provides a neat API for implementing common NLP techniques like noun-phrase extraction, POS Tagging, word inflection, sentiment analysis, parsing, WordNet, and n-grams.

Project Idea: Build a Review Classification Model using Gated Recurrent Unit

  1. PyNLPl

This Python library has a quirky pronunciation of ‘pineapple’. It is a library for performing NLP tasks of basic and advanced type. One can use it for building a simple language model, frequency list, and the extraction of n grams. One of the exciting features of this library is that it comes with an extensive library for working with FoLiA (Format for Linguistic Annotation) XML.

There are many more such libraries available in Python that are used for building NLP projects. To explore more such libraries and projects, check out ProjectPro’s repository of solved end-to-end projects in Data Science and Big Data.

 

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About the Author

Manika

Manika Nagpal is a versatile professional with a strong background in both Physics and Data Science. As a Senior Analyst at ProjectPro, she leverages her expertise in data science and writing to create engaging and insightful blogs that help businesses and individuals stay up-to-date with the

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