sharonowino/FUEL-PRICE-ANALYSIS-PREDICTION

This project aims to explore the fluctuations in fuel prices across different regions of Kenya between 2016 and 2024. Through analyzing historical data and building machine learning models, we aim to gain insights into the trends of fuel prices and predict future price movements in various regions of Kenya. # Fuel Price Analysis and Prediction in Kenya. # # Overview This project aims to explore the fluctuations in fuel prices across different regions of Kenya between 2016 and 2024. By analyzing historical data and building machine learning models, we aim to gain insights into the trends of fuel prices and predict future price movements in various regions of Kenya. Additionally, we aim to compare the performance of our machine learning models with the model used by the Energy and Petroleum Regulatory Authority (EPRA), the government body responsible for regulating fuel prices in Kenya. The best-performing machine learning model will be deployed as a web application for real-time fuel price predictions, and a Power BI dashboard will be built to visualize fuel price trends. # Problem Statement Fuel prices in Kenya have been fluctuating significantly over the years, influenced by various economic and political factors. These fluctuations have a direct impact on the cost of living, transportation, and overall economic stability in the country. Understanding the trends and patterns of fuel prices, predicting future price movements, and comparing the effectiveness of different prediction models are critical for both consumers and policymakers. This project aims to address the issue of fuel price fluctuation by analyzing historical data, building predictive models, and comparing our results with the EPRA’s official pricing model. Through the use of machine learning and advanced analytics, we will provide actionable insights that can help stakeholders make informed decisions regarding fuel pricing policies and strategies.