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Following Module 05's successful visual learning patterns: - Add ASCII diagrams for complex concepts - Natural markdown flow explaining what's about to happen - Visual memory layouts, data flows, and computation graphs - Enhanced test sections with clear explanations - Consistent with new MODULE_DEVELOPMENT guidelines Module 01 (Tensor): - Tensor dimension hierarchy visualization - Memory layout and broadcasting diagrams - Matrix multiplication step-by-step Module 02 (Activations): - Linearity problem and activation curves - Dead neuron visualization for ReLU - Softmax probability transformation Module 03 (Layers): - Linear layer computation visualization - Parameter management hierarchy - Batch processing shape transformations Module 04 (Losses): - Loss landscape visualizations - MSE quadratic penalty diagrams - CrossEntropy confidence patterns All modules tested and working correctly