This repository contains the source code of paper: "Semantic-based End-to-End Learning for Typhoon Intensity Prediction"
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Updated
Jan 8, 2020 - Jupyter Notebook
This repository contains the source code of paper: "Semantic-based End-to-End Learning for Typhoon Intensity Prediction"
Our project aims to help people come up with solutions to cope up with disasters before, during and after the disaster. We incorporate internet-less chatting, skin detection, fundraising, disaster prediction, live ground status and drones to deliver amenities into our project.
A Bidirectional LSTM model to classify whether a given tweet talks about a real disaster or not. This was my project in "CSC 522: Automated Learning and Data Analysis" course at NC State University.
An approach to solve the Kaggle Competition, Natural Language Processing with Disaster Tweets
A disaster prediction web application aided with AI to provide user with information on any upcoming natural disasters noted
This project involves building a machine learning model to classify tweets as disaster-related or not, using a dataset of 10,000 hand-labeled tweets to assist in real-time emergency detection.
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