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Rhythm-Finder is a unsupervised ML driven python powered web-application that can find the songs that suits you. It takes your basic data over music taste and gives you some song which you might like .
This section should list any major frameworks that you built your project using. Leave any add-ons/plugins for the acknowledgements section. Here are a few examples.
This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.
- We will be using the spotify dataset encoded in
csv
format. - Link of the dataset : Download Dataset
This is an example of how to list things you need to use the software and how to install them.
- Install Python on System : Download
- You can install Python via Anaconda Installer.
- Clone the repo
git clone https://github.com/gdscjgec/Rhythm-Finder.git
- Install dependencies
cd Rhythm-Finder pip install requirements.txt
- Open terminal and go to the folder using
cd
command example :cd <FILE_PATH>
- Run the command
streamlit run app.py
Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.
For more examples, please refer to the Documentation
See the open issues for a list of proposed features (and known issues).
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Add your Changes (
git add .
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE
for more information.
Mail us at - [email protected]