Welcome to the Hackathon project repository! This project was developed during Sagarmatha Hacks 2023, where we aimed to create a specific model that could potentially save lives. The project addresses the increasing mortality rate due to landslides and leverages an intelligent system that can predict and detect potential landslides using machine learning and geospatial data to provide a solution.
Hackathon Machine Learning is designed to facilitate machine learning exploration during hackathons. Whether you are a beginner or an experienced data scientist, this repository provides a set of tasks and a dataset to help you get started with building machine learning models for specific challenges.
The repository includes various machine learning tasks that cover a range of topics, such as classification, regression, and clustering. Each task is designed to be a standalone challenge that participants can work on during a hackathon. Feel free to choose the task that aligns with your interests or the hackathon theme.
The dataset for each task is provided within the respective task's directory. It includes the necessary data for training and evaluating machine learning models. Please refer to the documentation in each task directory for details on the dataset and the specific challenge.
Make sure you have the following dependencies installed:
- Python 3.x
- Jupyter Notebook (if using notebooks)
- NumPy
- Pandas
- Scikit-learn
- Matplotlib
- Seaborn
If you would like to contribute to this project, please follow these guidelines:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Make your changes and submit a pull request.
- Clearly document any changes or additions you make.
This project is licensed under the MIT License. Feel free to use, modify, and distribute the code as needed. Refer to the LICENSE file for more details.