Time series are everywhere: energy demand, weather, hydrology, finance, transportation, industrial systems, and many other domains. Behind these sequences lies a central scientific question: how can we infer tomorrow from yesterday?
This project is dedicated to the practical exploration of time series forecasting, with a strong emphasis on methodological rigor, interpretability, and real-world applications. In the coming months, this site will gradually be enriched with tutorials, technical articles, experiments, and case studies covering statistical models, feature engineering, hybrid architectures, optimization, and operational forecasting.