Spotify-Song-Recommendation-System

Spotify Song Recommendation System

Certainly! Below is a detailed README file template tailored for your project:

Spotify Song Recommender

The Spotify Song Recommender is a web application that provides song recommendations based on genre similarity and popularity. It utilizes data analysis techniques and cosine similarity calculations to offer personalized music suggestions to users.

Project Overview
Installation
Usage
File Structure
Contributing
License

Project Overview

The Spotify Song Recommender aims to enhance the music discovery experience for users by recommending songs that are similar in genre or have high popularity ratings. It leverages Spotify's extensive music database and implements algorithms to analyze user preferences and provide relevant suggestions.

Features of the Spotify Song Recommender include:

Genre-based Recommendations: Provides recommendations based on genre similarity, allowing users to explore songs similar to their preferred genres.
Popularity-based Recommendations: Offers recommendations based on song popularity, highlighting trending and popular tracks.
Interactive User Interface: The web application interface allows users to input a track name and receive tailored recommendations instantly.
Data-driven Approach: Utilizes data analysis techniques, including TF-IDF for genre similarity and cosine similarity calculations, to generate accurate recommendations.

Installation

To use the Spotify Song Recommender, follow these installation steps:

Clone the repository to your local machine:

git clone https://github.com/MihirSonawane1908/spotify-song-recommender.git

Navigate to the project directory:
```
cd spotify-song-recommender
```
Install the required dependencies using pip:
```
pip install -r requirements.txt
```
Run the Flask application:
```
python app.py
```
Access the web application through your browser at http://localhost:5000.

Usage

To use the Spotify Song Recommender:

Enter a track name in the search bar on the web application's homepage.
Click the "Search" button to receive recommendations.
Explore the genre-based and popularity-based recommendations provided on the results page.
Enjoy discovering new music that matches your preferences!

File Structure

The project's file structure is organized as follows:

spotify-song-recommender/
│
├── static/
│   ├── styles.css
│   └── main.js
    |__ style1.css
│
├── templates/
│   └── index.html
    |__ login.html
    |__ signup.html
│
├── app1.py
├── sampled_data.csv
├── README.md
├── requirements.txt
└── LICENSE

static/: Contains CSS and JavaScript files for styling and interactivity.
templates/: Contains the HTML template for the web application.
app.py: Flask application script containing route definitions and logic.
cosine_similarity.py: Module for calculating cosine similarity between songs.
sampled_data.csv: CSV file containing sampled data for genre similarity and popularity.
README.md: This README file providing information about the project.
requirements.txt: Lists all required Python packages for installation.
LICENSE: License file specifying the terms under which the project is distributed.

Contributing

Contributions to the Spotify Song Recommender project are welcome! To contribute:

Fork the repository and create a new branch for your feature or bug fix.
Make your changes and ensure the code passes all tests.
Submit a pull request with a clear description of your changes and their purpose.
Follow the code style and guidelines specified in the project.

Please report any issues or bugs by opening an issue on the GitHub repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Feel free to modify and add more specific details as needed to make the README file comprehensive and tailored to your project.

MihirSonawane1908/Spotify-Song-Recommendation-System