Temporal Fusion Transformer

The Temporal Fusion Transformer (TFT) is a sophisticated machine learning model designed to predict future values in time series data, like sales or weather patterns. It intelligently combines information from past data, identifies important features, and considers how different factors interact over time. Using attention mechanisms, TFT focuses on the most relevant information at each step, improving accuracy and interpretability. This makes it particularly powerful for complex forecasting tasks involving multiple related variables, helping businesses and researchers make data-driven decisions based on accurate, timely predictions.