World Energy

---

Process

Step 1: Collecting the data and adding features to give models dimensions

Step 2: Data cleaning, transforming, and loading through Python

Step 3: Built a one-step-ahead forecast to train the data on the historical data

Step 4: Built a multi-step forecast based upon a 5-year window of moving averages to test the data

Step 5: Ran the 4 different machine learning models (Multiple Linear Regression, Lasso, Ridge, and ElasticNet) on the Oil and Natural Gas predictions

Step 6: Created visualizations using Tableau

Step 7: Created webpages to display visualizations embeded from Tableau Public