Synthesis & Interpretability
Synthesis of the complete forward-backward computational graph, end-to-end mathematical compile traces, and mechanistic interpretability foundations.
01 • The Complete Neural Data Flow Graph
The Forward-Backward Computational Graph
Unify the forward pass, loss calculation, and backward backpropagation into a single directed acyclic graph and verify the closed-loop trace.
The Closed Learning Cycle on Paper
Execute a complete forward pass, loss calculation, backpropagation cycle, and second forward pass on paper to prove error reduction.
The Mathematical Compile Trace Audit
Perform an exhaustive compile trace verifying that every forward tensor and backward gradient calculation relies strictly on course prerequisites.
Operating the Grand Capstone Engine
Operate the Bycroft-grade interactive macro-system to inspect real-time tensor registers and verify hand-calculated values at 60fps.
The Complete Neural Data Flow In Practice
Master complete end-to-end forward and backward passes, loss calculations, gradient attributions, and parameter updates through manual calculations.
02 • Interpretability of Neural Networks
The True Nature of the "Black Box"
Examine the boundary of transparent arithmetic and latent representations, explore mechanistic interpretability, and bridge vanilla MLPs to Transformers.
Interpretable Weights vs. Latent Geometry
Contrast human-interpretable feature weights against high-dimensional latent coordinate geometry inside multi-layer representations.
Mechanistic Interpretability Foundations
Analyze modern scientific methods for probing, ablating, and reverse-engineering the semantic roles of hidden neurons in deep networks.
From Vanilla MLPs to Modern Transformers
Synthesize core vanilla MLP principles and establish the structural bridge to token embeddings, self-attention, and large language models.
Neural Interpretability In Practice
Master latent representation geometry, linear separability, feature ablation, and Transformer MLP sublayer calculations through manual hand traces.