10 Useful Tools For Natural Language Processing

1. Scikit-learn

Scikit-learn has been around for more than a decade and is now widely used by lots of in-house data science teams. It provides a platform for not only training and testing NLP models but also NLP and NLU workflows. It has its own extensive library of models in addition to working well with many of the libraries such as NLTK. Many NLP and NLU projects involve classic workflows of feature extraction, training, testing, model fit, and evaluation, meaning scikit-learn’s pipeline module fits this purpose well.

Working With Text Data - scikit-learn 0.24.1 documentation

2. NLTK

The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language. With NLTK, we can search for a word meaning by using a built-in lexical database called WordNet. WordNet presents nouns, verbs, adjectives, and adverbs grouped in sets of cognitive synonyms — synsets — with each synset representing a distinct concept. NLTK has been called “a wonderful tool for teaching, and working in…