About the Project

Project Overview

The primary objective of the SARIMAX project was to understand how SARIMAX modeling can be utilized to predict daily transportation demands. This initiative focused on applying theoretical concepts in a practical scenario to forecast public transport usage, learning the intricacies of time series analysis and predictive modeling in the process.

Skills Used
  • Time Series Analysis
  • SARIMAX Modeling
  • Pandas & Matplotlib
  • Python Programming
  • Statistical Data Analysis
Problem Identification

The challenge was not only in predicting transport demands but also in understanding and structuring complex datasets that influence prediction accuracy.

Mission

To leverage SARIMAX for educational purposes, enhancing my understanding of its predictive capabilities and the factors that affect its performance in real-world applications.

Challenges Faced

Integrating and analyzing complex, multi-dimensional data posed significant challenges, impacting the model's accuracy due to the inherent limitations of the data structure and available variables.

Outcome

Although the SARIMAX model did not achieve enough accuracy, the learning experience was invaluable. It provided deep insights into the challenges of predictive modeling and the critical importance of data quality and structure.