Skip to content

Language modele that detect if a song include potential "caracteristic" of a HIT / top song

Notifications You must be signed in to change notification settings

AlanJumeaucourt/hitorflop

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Hit or Flop 🎵

A production-ready AI system that uses convolutional neural networks to predict whether a song has the characteristics of a hit or a flop.

🚀 Features

  • Real-time song prediction using Spotify's track data
  • Interactive web interface
  • Integration with Spotify's API
  • Containerized application using Docker
  • Neural network model trained on historical hit data

🔍 How It Works

The system analyzes various musical features of a track (such as danceability, energy, tempo, etc.) using Spotify's audio features API and processes them through our trained neural network to predict its hit potential.

🎯 Demo

Homepage

Homepage

🛠️ Tech Stack

  • Frontend: React, TypeScript, Tailwind CSS
  • Backend: Python, FastAPI
  • AI Model: TensorFlow, Keras
  • Infrastructure: Docker, Docker Compose

📝 Model Training

The neural network model was trained using a comprehensive dataset of historical music data. You can find the training notebook and methodology on Kaggle: Spotify Hit or Flop Training Notebook

🚀 Getting Started

  1. Clone the repository
  2. Create a .env file with your Spotify API credentials
  3. Run with Docker Compose: