## Flowchart: Machine Learning Model Weight Update Process ### Overview The diagram illustrates a technical workflow for a machine learning model, focusing on weight initialization, inference, prediction error calculation, and controlled weight updates. It combines mathematical operations (e.g., linear scaling, mapping) with algorithmic steps (e.g., reset, read, write) to optimize model parameters. --- ### Components/Axes 1. **Left Section (Initialization & Inference)**: - **Initialization**: Block labeled "RESET G⁺ and G⁻". - **Inference**: - **Readout Inference**: Block with formula `σ[∑xᵢ(Gᵢⱼ⁺ − Gᵢⱼ⁻)]`, where `σ` is the sigmoid