The uploaded codes help to classify emails into spam and non spam classes by using Support Vector Machine classifier.

A module for creating stopword lists for any language, based on a set of documents.

Bangla NLP toolkit.

Plotly-Dash NLP project. Document similarity measure using Latent Dirichlet Allocation, principal component analysis and finally follow with KMeans clustering. Project is completed with dynamic visual interaction.

PHP StopWords removal library with support for multiple languages.

Visualizing word embeddings generated by GloVe and Word2Vec models using the t-SNE algorithm

This code is used to remove stopwords using Tala stopwords library for Indonesia. Very useful for text processing

Music is a powerful language to express our feelings and in many cases is used as a therapy to deal with tough moments in our lives or as a tool to celebrate the joyous moments. The different sounds, rhythms, and effects used in music are capable to modify our emotions for a moment, but there’s a component that sometimes goes unnoticed when we a…

A python package to be used in removing stopwords in different languages.

Created a Python library specifically for Traditional Chinese stopwords and punctuations removal

Performed Sentiment Analysis on Elon Musk's Tweets. Extracting Positive or Negative Sentiment.

YouTube Comments as a Corpus of Sentiment Analysis is the final project of DFLL672 Corpus Linguistics.

This Python code retrieves thousands of tweets, classifies them using TextBlob and VADER in tandem, summarizes each classification using LexRank, Luhn, LSA, and LSA with stopwords, and then ranks stopwords-scrubbed keywords per classification.

Android Sastrawi is a Natural Language Processing Toolkit for Bahasa Indonesia

This project is a demonstration of how Natural Language Processing (NLP) techniques can be used to perform sentiment analysis on stock news headlines

Crawling news and information website and anticipating the likelihood of its virality.

Named Entity recognition and emotion mining on Apple Macbook reviews.

K-means clustering of texts (survey answers) using word-embeddings, finding optimal elbow-point, and averaging multiple-word expressions.

Basics of Natural Language Processing