/Music_Genre_Classification

Music Genre Classification

Primary LanguageJupyter Notebook

Music_Genre_Classification (K-POP VS Western)

A complete machine learning pipeline from scraping music data to modelling a music genre classifier and deployting it.

The deployed web app is live at https://jihun-kpop-western-classifier.herokuapp.com/ .

Project Scope

  • Data Collection (Spotify API for Music Features and Genius API for Song Lyrics)

  • Data Cleaning (Treating Null Values Inside the Dataset, etc.)

  • Exploratory Data Analysis

  • Machine Learning Modelling and Testing (Classification Model)

  • Model Deployment

  • Technologies Used

  • Data Collection & Cleaning

    • Song Features
      • Spotipy API (For Collecting Music Features)
      • Pandas (Inserting the data into a dataframe, Dropping Duplicate Rows and Exporting the data as CSV)
    • Song Lyrics
      • Requests (Send request to Genius API for song info)
      • Googlesearch (If requests is unable to get the song info, a google search will be performed to find the link of the music in Genius.)
      • BeautifulSoup (With the URLs returned from either Requests or Googlesearch, BS will scrape the lyrics of the song.)
      • Pandas (Used to insert the lyrics into a dataframe)

  • Exploratory Data Analysis

    • Pandas (Analyzing, Filtering, Summary)
    • Matplotlib, Seaborn (Visualization)
    • Statsmodels (ANOVA)
    • Scipy (Mannwhitneyu)
    • Itertools (For different Group Combinations)

  • Machine Learning Modelling

    • Sci-Kit Learn
    • XGBoost
    • Light GBM

  • Model Deployment

    • Streamlit