This is the final project for the class Machine Learning in Python. Here you can find our code in Python and the report of the project.

This project uses decision trees, XGBoost and random forest algorithms for classifying music samples given from a dataset. It was developed in a jupyter notebook using os, sys, numpy, pandas, seaborn and matplotlib libraries.

The structure of the project goes as follows:

Project Description Methodology Exploratory data analysis Feature engineering and data cleaning Build the machine learning model Evaluate the machine learning model Hyperparameter tuning Results Conclusion

Team members:Shania Martinez, Samuel Russo, Jesús Ortega, Mauricio Gonzalez

Special thanks to professor Sarah for all her help. https://github.com/shaq31415926