The objective of the project is to predict whether a particular tweet, of which the text (occasionally the keyword and the location as well) is provided, indicates a real disaster or not. We use various NLP techniques and classification models for this purpose and objectively compare these models by means of appropriate evaluation metric.

A disaster management system integrating deep learning, NLP, and real-time web solutions to predict cyclone intensities, provide multilingual alerts, offer safety paths, and ensure enhanced disaster preparedness and communication.

Real or Not? NLP with Disaster Tweets is a kaggle competition problem where we have to predict which Tweets are about real disasters and which ones are not. I participated in the Kaggle competition and solved the problem using Machine Learning and Natural Language processing. This repository contains all the code regarding the solution that I submitted at that time.

Kaggle NLP challenge to predict disasters

Using NLP to predict whether a tweet is about a disaster or not

Project for LTAT.02.002 Introduction to Data Science course. NLP machine learning to predicts whether tweets are about natural disasters or not.

This code is based on the kaggle competition Real or Not? NLP with Disaster Tweets . The aim of this competition is to predict a tweet as a disaster related tweet or not .

AlertSphere is a machine learning-based system designed to predict whether a given tweet indicates a disaster. It utilizes natural language processing (NLP) techniques to analyze the text content of tweets and classify them as either disaster-related or not.

Created a web app to display disaster response categories predicted based on a random forest classifier trained over an NLP pipeline that cleans, stems, lemmatize, and vectorize the provided data

In this KAGGLE competition, we are required to build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t. We have access to a dataset of 10,000 tweets that were hand classified to solve this NLP problem. Machine Learning Model was built which predicted with accuracy of ~80% to solve this NLP problem

This project tackles the classic Kaggle "Disaster Tweets" classification problem. The goal is to build a machine learning model that accurately predicts whether a tweet is about a real disaster or not. This project explores a comprehensive NLP workflow, starting from data exploration and preprocessing to feature engineering, model training,and eval

In this Problem, we build a machine learning model that predicts which Tweets are about real disasters andwhich one’s aren’t. We have a dataset of 10,000 tweets that were hand labeled.This is an NLP problem andwe will be using various methods to determine the accuracy with which we can predict this.

REAL OR NOT? NLP WITH DISASTER TWEETS In this project we build Machine learning models to predict which Tweets are about real disasters and which ones aren't. It is a Kaggle challenge (https://www.kaggle.com/c/nlp-getting-started) about NLP, and it was the project we developed in the Factored AI Sessions. (Jan - Apr, 2020) Technologies: Python, Colab Notebooks, Machine Learning, TensorFlow Hub. Metrics: F1 Score F1 = 2 * (precision * recall) / (precision + recall) Models LogisticRegression RandomForestClassifier SVC Embedding methods Bags of words [sklearn] TF-IDF [sklearn] Universal Sentence Encoder (TensorFlow Hub) [https://tfhub.dev/google/universal-sentence-encoder/4] Hyperparameter Tuning Randomized Search Team 5: Laura Salazar Ramírez - Wilmar González Medina - Johan E. López Cifuentes Thanks to the Factored AI team, especially Santiago Hernández Torres, Carlos Miguel Patiño and Camilo Velasquez.

Real-or-Not-NLP-with-Disaster-Tweets: 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). But, it’s not always clear whether a person’s words are actually announcing a disaster. Take this example: The author explicitly uses the word “ABLAZE” but means it metaphorically. This is clear to a human right away, especially with the visual aid. But it’s less clear to a machine. In this competition, you’re challenged to build a machine learning model that predicts which Tweets are about real disasters and which one’s aren’t. You’ll have access to a dataset of 10,000 tweets that were hand classified. If this is your first time working on an NLP problem, we've created a quick tutorial to get you up and running. Disclaimer: The dataset for this competition contains text that may be considered profane, vulgar, or offensive. Acknowledgments This dataset was created by the company figure-eight and originally shared on their ‘Data For Everyone’ website here. Tweet source: https://twitter.com/AnyOtherAnnaK/status/629195955506708480

Project to enhance my skills in NLP, ML, DL and development web with Flask

NLP model to predict disaster tweets using LSTM

NLP model to predict disaster tweets using LSTM

This is the solution of Top 7% of NLP Disaster Prediction Competition on Kaggle

NLP model to predict legitimacy of disaster tweets with 78% accuracy

it is an NLP project to predict disaster tweet or not

Apply recursive neural net to predicting natural disasters from tweet NLP in Kaggle Disaster Tweets Competition

This is an NLP project used to predict disaster tweets or not.

Kaggle Project to use NLP to predict which tweets refer to an actual disaster.

using NLP approach to predicting if tweets are disaster related tweet or not

Training the DistilBERT NLP to predict which tweets are about a real disaster.

Using NLP to predict if a tweet about a disaster is Real or Fake

NLP Sentiment Analysis - Supervised ML techniques to predict disaster status of a given tweet

NLP classification for kaggle competition to predict whether a tweet is disaster using TensorFlow.

Used NLP to differentiate and predict real disaster tweets vs common language on twitter

This NLP project aims to predict whether a tweet describes a real disaster or not.