This project applies supervised and unsupervised classification techniques to information scraped from lyrics.com to determine musical genre tag. The Lyrics.com data set contains roughly 1 million songs, 10% of which have preassigned genre tags.
The main notebook detailing the analysis process is available in this repository HERE.
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├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
Project based on the cookiecutter data science project template. #cookiecutterdatascience