📄️ Model strategy
Our predictive modeling strategy for the Samurai Predictive Event Model involves multi-step data transformation to ensure high-quality inputs. We integrate both real-time and batch processing to capture immediate and aggregate user behavior patterns. The current state of the model architecture is based on Long Short-Term Memory (LSTM) networks, which are ideal for modeling sequential data. We're committed to experimenting with other model architectures. This document outlines the key model design strategies and sets the stage for detailed model architecture considerations.