Twitter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programatically monitoring Twitter (i.e. disaster relief organizations and news agencies).
The goal of this project was to gain insights on such tweets and perform analysis on the data to predict whether a given tweet was about a disaster or not.
This was the first time I had worked with Natural Language Processing. Through this project, I was introduced to nltk, a powerful toolkit for for Natural Language processing. https://www.nltk.org/
Also, I learnt and understood the working and mathematics behind few machine learning models like Bernoulli Naive Bayes, Stochastic Gradient Descent, Support Vector Machines, etc.