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All Projects → gdscjgec → Rhythm-Finder

gdscjgec / Rhythm-Finder

Licence: MIT license
ML-powered Music Recommendation Engine

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python
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machine-learningrecommendation-enginehacktoberfesthacktoberfest2021

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Rhythm Finder

An awesome README template to jumpstart your projects!
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View Demo · Report Bug · Request Feature

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact

About The Project

![Product Name Screen Shot][product-screenshot]

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 .

Built With

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.

Getting Started

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.

Dataset

  • We will be using the spotify dataset encoded in csv format.
  • Link of the dataset : Download Dataset

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

Installation

  1. Clone the repo 
    git clone https://github.com/gdscjgec/Rhythm-Finder.git
  2. Install dependencies 
    cd Rhythm-Finder
pip install requirements.txt
  3. Open terminal and go to the folder using cd command example : cd <FILE_PATH>
  4. Run the command 
    streamlit run app.py

Usage

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

Roadmap

See the open issues for a list of proposed features (and known issues).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch ( git checkout -b feature/AmazingFeature )
  3. Add your Changes ( git add . )
  4. Commit your Changes ( git commit -m 'Add some AmazingFeature' )
  5. Push to the Branch ( git push origin feature/AmazingFeature )
  6. Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Mail us at - [email protected]

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].