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here you can see how to tokenize the data: 1) how to use the useful libraries for nlp 2) how to clean data 3)how to make normalization and removing stop words 4) how to make lemmatization and stemming
This repo contains basic tutorial on how to get started with the fundamentals of NLP and a few projects like Twitter Data Sentiment Analysis, Restaurant Reviews, etc
The Text to Sign Language Converter is a mobile app built with Flutter and Dart. It turns text into Sign Language GIFs, aiding those with hearing impairments or sign language users.
Designed a mini-search engine using English language Wikipedia corpus of size 80 GB by creating inverted indices. It gives you top search result related to given query words.
A NLP app built with streamlit framework using SpaCy for Tokenization,Lemmatization,Parts of Speech (POS) Tagging and Named Entity Extraction(NER),TextBlob for Sentiment Analysis.
Text preprocessing, indexer constructions, and search engines implementation for information retrieval. Performance analysis done by measuring the construction time of indexers.
# **The BTDS Discord Bot, a versatile and interactive bot, is designed to enhance the functionality and engagement within a Discord server. Developed using Python and the Nextcord library, this bot offers a wide array of features ranging from entertainment, utility, finance, to user engagement.**