A short django project to preprocess text data for NLP problems.
-
Updated
Feb 18, 2023 - Python
A short django project to preprocess text data for NLP problems.
Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.
Repository containing other projects.
Predict stock market using top news headlines
Classification of Disaster Tweets as REAL or FAKE using Machine Learning
Leveraging 21,000+ Amazon Reviews to conduct Natural Language Processing (NLP), Sentiment Analysis & Supervised Machine Learning to select the best specialty ice cream flavor for our expansion.
Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.
Sentiment Analysis - Airline Tweets using NLP preprocessing, ML algorithms - Logistic regression, XGboost & Naive bayes
Natural language processing involves the reading and understanding of spoken or written language through the medium of a computer. This includes, for example, the automatic translation of one language into another, but also spoken word recognition, or the automatic answering of questions.
This repository contains code for preprocessing natural language data for use in NLP applications.
Alexa Sentiment Analysis interprets user emotions from their interactions with Amazon's virtual assistant. By analyzing speech patterns and language, it categorizes sentiments as positive, negative, or neutral. This enhances Alexa's responses, ensuring more personalized and effective interactions.
This repository contains introductory notebooks for text mining and web scrapping.
A NLP for summarization, tokenazition of characters, words, & sentences, spell check, removal of tags, numbers, stopwords & punctuation, and topic detection.
Problem Statement: Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.
Add a description, image, and links to the lemmetization topic page so that developers can more easily learn about it.
To associate your repository with the lemmetization topic, visit your repo's landing page and select "manage topics."