Reco

Reco is an AI-based Android application developed to recommend mood-based songs from a dataset of 52,000+ songs. The app includes a clean and simple chatbot-like feature that helps users discover and play songs.

Table of Contents

• Screenshots
• Installation
• Usage
• KNN Algorithm
• Contribution Guidelines

Screenshots

Installation

Manual Installation

1. Clone the repository to your local machine:

git clone https://github.com/your-username/Reco.git

2. Open the project in Android Studio.

3. Build and run the app on your Android device.

APK Installation

1. Download the APK file from the following link: Download.

2. Transfer the downloaded APK file to your Android device.

3. On your Android device, locate the APK file and tap on it to install Reco.

4. Once the installation is complete, you can launch the app and start using it.

Usage

To use Reco, follow these instructions:

1. Launch the app on your Android device.

2. Explore the chatbot-like feature to discover songs based on your mood.

3. Interact with the app to get song recommendations.

4. Enjoy listening to the recommended songs.

KNN Algorithm

Reco utilizes the K-Nearest Neighbors (KNN) algorithm to recommend mood-based songs. The KNN algorithm is a simple and intuitive machine learning algorithm that classifies new data points based on the similarity of their features to existing labeled data points. In Reco, the algorithm considers various musical features, such as tempo, mood, genre, and instrumentation, to determine the nearest neighbors and recommend relevant songs.

Contribution Guidelines

We welcome contributions from everyone. To contribute to Reco, please follow these steps:

1. Fork the repository to your own GitHub account.

2. Clone the forked repository to your local machine:

git clone https://github.com/your-username/Reco.git

3. Create a new branch for your contribution:

git checkout -b feature/your-feature

4. Make the necessary changes, improvements, or fixes.

5. Test the changes thoroughly to ensure they do not introduce any regressions.

6. Commit your changes and push them to your forked repository.

7. Submit a pull request from your forked repository to the main Reco repository.

8. Provide a clear and detailed description of your changes in the pull request.

9. Participate in the discussion and address any feedback or comments received.

Thank you for considering contributing to Reco! Together, we can make the project even better.