digital-house-challenge-3

Setup

1. Download project with git clone https://github.com/[username]/digital-house-challenge-3.git
   • To update changes from GH into local repo: git pull origin master
   • Save local changes to github with: git add [filenames] git commit -m '[Commit message]' Git push origin master
2. Download fma dataset fma_metadata.zip in data/ folder
3. Python environment used: dhdsblend
   • To activate run conda activate dhdsblend
4. Install additional python libraries pip install -r requirements.txt

To use Spotify API, create file named 'config.ini' with the following information:

[SPOTIFY]
username = 
scope = user-read-private user-read-playback-state user-modify-playback-state
SPOTIPY_CLIENT_ID = 
SPOTIPY_CLIENT_SECRET = 
SPOTIPY_REDIRECT_URI = https://google.com.ar

Additional Python libraries

1. Spotipy Spotify.py is a modern, friendly, and Pythonic API library for the Spotify API.

2. Librosa It is a Python module to analyze audio signals in general but geared more towards music.

Datasets a explorar:

• GTZAN Music Genre Classification
  • Notebook > Genre Classification using Deep Learning
• FMA: A Dataset For Music Analysis
• Podcasts dataset
• Spotify Playlists
• Spotify Datasets

Notebooks

• Music Genre Classification with Python

Data augmentation

• Spotify API