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.

This repository contains introductory notebooks for text mining and web scrapping.

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.

Classification of Disaster Tweets as REAL or FAKE using Machine Learning

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.

A NLP for summarization, tokenazition of characters, words, & sentences, spell check, removal of tags, numbers, stopwords & punctuation, and topic detection.

Repository containing other projects.

Predict stock market using top news headlines

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.

A short django project to preprocess text data for NLP problems.

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.

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.

Sentiment analysis of Steve Jobs speech