Million Song Dataset

Context

Songs, like any other audio signal, feature distinctive fundamental frequencies, timbre components, and other properties. Each song is unique in these respects, which is why they can be patterned.

Objective

Your task is to use machine learning models to predict the release year (between 1922 and 2011) of a song that is described by 90 attributes of average timbre and covariance.

Evaluation Criteria

Once you generate and submit the target variable predictions on evaluation dataset, your submissions will be compared with the true values of the target variable. 

The True or Actual values of the target variable are hidden on the DPhi Practice platform so that we can evaluate your model's performance on unseen data. Finally, a Root-Mean-Squared-Error (RMSE) score for your model will be generated and displayed.