NLP : Projects Building Libraries
by akshara 
Updated: Jun 17, 2022
Guide Kit
NLP stands for Natural Language Processing, which is a part of Computer Science, Human Language, and Artificial Intelligence. It is the technology that is used by machines to understand, analyze, manipulate, and interpret human languages. It helps developers to organize knowledge for performing tasks such as translation, automatic summarization, Named Entity Recognition (NER), speech recognition, relationship extraction, and topic segmentation.
Components of NLP are:
Some Important Projects of NLP are:
1) Sentiment analysis for marketing
This project helps find out how customers evaluate competitor products, which is what they like and dislike. Learning what customers like about competing products can be a great way to improve our own products, so this is something that many companies are actively trying to do.2) Toxic comment classification
This project helps create a model that helps classify comments into different categories. Comments on social media are often abusive and insulting. Organizations often want to ensure that conversations don’t get too negative. Hence this provides a solution to avoid that.3) Create text summarizer
This project is a way of identifying meaningful information in a document and summarizing it while conserving the overall meaning. The purpose is to present a shorter version of the original text while preserving the semantics.4) Quora question pair similarity
Quora is a question-and-answer platform where you can find all sorts of information. Every piece of content on the site is generated by users, and people can learn from each other’s experiences and knowledge. This project deals with a task that requires finding high-quality answers to questions which will result in the improvement of the Quora user experience from writers to readers.5) Paraphrase detection task
Paraphrase detection is a task that checks if two different text entities have the same meaning or not. This project has various applications in areas like machine translation, automatic plagiarism detection, information extraction, and summarization. The methods for paraphrase detection are grouped into two main classes: similarity-based methods, and classification methods.Some Important Libraries are:
NLTK
NLTK has various different libraries for performing text functions ranging from stemming, tokenization, parsing, classification, semantic reasoning, etc. The most important thing is that the NLTK is free and open-source. This toolkit is a perfect option for natural language processing.
TEXTBLOB
TextBlob is a Python library that is created for the express purpose of processing textual data and handling natural language processing with various capabilities such as noun phrase extraction, tokenization, translation, sentiment analysis, part-of-speech tagging, lemmatization, classification, spelling correction, etc. TextBlob is a perfect option for beginners to understand the complexities of NLP.
TextBlobby sloria
8472 Version:0.7.0Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
TextBlobby sloria
Python 8472 Version:0.7.0 License: Permissive (MIT)
GENSIM
Gensim is a Python library that is specifically created for information retrieval and natural language processing. Gensim is dependent on NumPy and SciPy which are both Python packages for scientific computing. This library is also extremely efficient and it has top-notch memory optimization and processing speed.
SPACY
spaCy is a natural language processing library in Python. spaCy is written in memory-managed Cython which makes it extremely fast. spaCy provides support for various features in NLP such as tokenization, named entity recognition, Part-of-speech tagging, dependency parsing, sentence segmentation using syntax, etc.
spaCyby explosion
25599 Version:v3.5.1💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCyby explosion
Python 25599 Version:v3.5.1 License: Permissive (MIT)
VOCABULARY
Vocabulary is basically a dictionary for natural language processing in Python. Using this library, you can take any word and obtain its word meaning, synonyms, antonyms, translations, parts of speech, usage example, pronunciation, hyphenation, etc. Vocabulary is also very easy to install and it's extremely fast and simple to use.
vocabularyby tasdikrahman
548 Version:1.0.4[Not Maintained anymore] Python Module to get Meanings, Synonyms and what not for a given word
vocabularyby tasdikrahman
Python 548 Version:1.0.4 License: Permissive (MIT)
POLYGLOT
Polyglot is a free NLP package that can support different multilingual applications. Polyglot supports various features inherent in NLP such as Language detection, Named Entity Recognition, Sentiment Analysis, Tokenization, Word Embeddings, Transliteration, Tagging Parts of Speech, etc. It provides different analysis options in natural language processing.
polyglotby aboSamoor
2119 Version:CurrentMultilingual text (NLP) processing toolkit
polyglotby aboSamoor
Python 2119 Version:Current License: Others (Non-SPDX)
PATTERN
Pattern is a Python web mining library and it also has tools for natural language processing. Pattern can manage all the processes for NLP that include tokenization, translation, sentiment analysis, part-of-speech tagging, lemmatization, classification, spelling correction, etc.
patternby clips
8437 Version:3.7-betaWeb mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
patternby clips
Python 8437 Version:3.7-beta License: Permissive (BSD-3-Clause)