About the dataset

This database contains 90 attributes of average timbre and covariance. The target variable refers to the year of release per song, between 1922 and 2011.

Download the training set from the following link: https://drive.google.com/file/d/1EjnfKFByNtRbcumGF-cDVLHVM5VPnb4h/view, unzip the file and load the training data in your jupyter notebook, use the below command:

import pandas as pd
songs_data  = pd.read_csv("Training_set_songs.csv" )

Data Description

TA01 to TA12 – Timbre avarages
TC01 to TC78 – Timbre covariances
Year – Release year

Evaluation Dataset

Download the testing set from the following link: https://drive.google.com/file/d/1EjnfKFByNtRbcumGF-cDVLHVM5VPnb4h/view, unzip the file and load the testing data in your jupyter notebook, use the below command:

songs_data = pd.read_csv("Testing_set_songs.csv" )

Here the target column is deliberately not there as you need to predict it.

References

This dataset is adapted from:

T. Bertin-Mahieux. UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science. 2019. Available at: http://archive.ics.uci.edu/ml/datasets/YearPredictionMSD.

Million Song Dataset

Challenge Starts

Challenge Ends