Top 3 Natural Language Processing Libraries
Tags: machinelearning
Published: 2019-07-08 12:37:33

Natural Language Processing (NLP) is the technology that powers chatbots, voice assistants, predictive text, among other text/speech applications that we interact with daily.
![nlp libraries](https://thepracticaldev.s3.amazonaws.com/i/v2492k4wiuko3npg6mlw.jpg)

## What Is an NLP Library?

An NLP library is a toolkit that processes unstructured data from different places allowing us to understand it and gain valuable insight. In this article, we review the top 3 NLP libraries to ensure that you settle on the right one:

## Natural Language Toolkit (NLTK)

Natural Language Toolkit (NLTK) is arguably one of the most comprehensive NLP libraries out there. It implements virtually any component of natural language processing you want, for example, stemming, tokenization, classification, parsing, semantic reasoning, and tagging. Moreover, often, there is more than one implementation for each component, thus enabling you to pick the exact methodology or algorithm you want to use. Apart from that, it supports several languages.

Nonetheless, given that NLTK represents data as strings, which is excellent for simple constructs, it makes it challenging to implement some advanced functionalities. Apart from that, documentation on the library is quite dense - but you can still use the [NLTK book](http://www.nltk.org/book_1ed/) to find your way around. Another notable downside is that, when compared to other tools, NLTK is a little bit slower.
With all that said, NLTK remains an excellent library for exploration, experimentation, and applications that require a specific combination of algorithms.

## TextBlob

An extension of NLTK, you can use TextBlob to access several of NLTK’s functions in a simple way. Furthermore, TextBlob comes with functionality from the Pattern library. If you are a beginner, this is an excellent tool to use and can help in the production of apps that do not require to be overly functional.
That considered, TextBlob is used widely and is right for small projects.

## SpaCy

NLTK may become slow and cumbersome when handling more complicated business applications. SpaCy is a step-up from NLTK as it gives users a much smoother, quicker, and more efficient experience. This open source natural language processing library is purposely developed for business activities such as comparing product profiles, client profiles, and text files.

SpaCy is an excellent choice when conducting market research and collecting insights because of its aspect-based sentiment analysis, named-entity recognition, and optimization of conversational user interface abilities. This library also works well with word vectors such as doc2vec and word2vec, which is not possible in CoreNLP or OpenNLP.

Overall, SpaCy stands out from other NLP libraries like Stanford, Apache OpenNLP, and CoreNLP in that all of the functions are combined to create ready building blocks. Therefore, you save time by not needing to pick individual modules by yourself. SpaCy is best used in data extraction and analysis, text summarization, and sentiment analysis.

## Final Word

NLP libraries are used in text data analysis to deriving useful business insights. However, there are many options out there. Making the right decision about which NLP library is best for your projects and business is about knowing which options are available and how they compare to each other. More NLP frameworks you may find in ["NLP Tools review"](https://theappsolutions.com/blog/development/nlp-tools/). Choose from these top-of-the-class libraries for more successful projects.