ds-simple-portfolio

Project 1: K-Pop Analysis

Overview

• Created a web application that returns the predicted number of hours one listens to K-pop on a daily basis using FLASK (MAE ~ 1.2 hours).

  

• Engineered features from the text of each column.

• Explored the data to analyze the relationships among the features (or variables).

  

  

• Built five different regression models - linear, lasso, ridge, random forest, and XGBoost.
• Optimized the random forest and the XGBoost model using GridsearchCV to find the optimal parameters.