Time Series Forecasting
Irtaza Ahmed Khan
Statistical Models
Regression Models
Deep Learning Models
Evaluation Metrics
I developed a comprehensive Time Series Forecasting system using the Darts framework in Python, designed to model and predict sales trends for a retail store. The project focused on experimenting with a wide range of forecasting techniques to identify the most accurate and efficient approaches for different data scenarios.
Statistical / Classic Models
• ARIMA
• Exponential Smoothing
• Prophet
Regression Models
• Linear Regression
• Random Forest
• LightGBM
• XGBoost
• CatBoost
PyTorch (Lightning) Based Models
• N-HiTS
• TCN
• Transformer
• D-Linear
• N-Linear
• TiDE
• TSMixer
By leveraging traditional statistical methods, machine learning regressors, and state-of-the-art deep learning architectures, this project highlights the scalability of Darts for handling complex forecasting tasks. The outcome was a flexible forecasting pipeline capable of adapting to varying demand patterns, ensuring more accurate, data-driven decision-making for inventory and business planning.
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Posted Feb 10, 2025
I developed a Time Series Forecasting system for a retail store using the Darts framework in Python. I used Statistical, Regression, and Deep Learning models.
