Crude Oil Price Prediction using Machine Learning Algorithms

Enormous swings price changes for crude oil can have a significant impact on the economy and on international politics. The ability to estimate crude oil prices accurately is crucial for making decisions in a variety of industries, including energy, finance, and policy. This study investigates the use of machine learning and time series analysis to estimate the price of crude oil. Our main goal is to use the Prophet time series forecasting model with the Random Forest Regressor to make predictions about future crude oil prices using previous price data. By taking advantage of elements including seasonality, past price trends, and outside influences, this study seeks to increase the accuracy of the pricing of crude oil projections.