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This is my third Machine Learning Project. This repository hosts the code and resources for the Nepal 2015 Earthquake building damage predictor, a part of the DrivenData Competitions. The project aims to predict the level of damage to buildings caused by the 2015 Gorkha earthquake in Nepal based on aspects like building structure and location.
This repository contains a Flask web application that uses a CatBoost regression model to predict earthquake magnitudes. The model is trained using a dataset containing various features related to earthquakes.
🌍 Welcome to the Earthquake Prediction Analysis Project! 🚀 This project aims to predict earthquake magnitudes using LSTM neural networks and analyze seismic data. Explore, analyze, and forecast earthquakes with ease! 📈🔮
This project aims to predict the magnitude and probability of Earthquake occurring in a particular region using the historic data with various machine learning models to find which model is more accurate to accomplish this task.