Notebook

1 Mathematical Background Review Oct 24, 2025

1 Set Theory & Probability I — Sets, axioms, conditional probability Oct 25, 2025 2 Set Theory & Probability II — Independence, total probability, Bayes' theorem Oct 26, 2025

0 Prologue — The Intellectual Genealogy of Deep Neural Networks Feb 23, 2026 I Mathematical Foundations — Linear algebra, calculus, probability & autodiff Feb 23, 2026 II The Multilayer Perceptron — Complete dissection from neuron to backprop Feb 23, 2026 III Convolutional Neural Networks — Complete dissection, im2col, landmark architectures Feb 23, 2026 IV Training Components — Loss functions, optimizers, regularization, BatchNorm Feb 23, 2026 V Computational Efficiency — FLOPs, memory, roofline model, quantization, scaling laws Feb 23, 2026 VI Advanced Topics — Transformers, RNNs, Lottery Ticket, MoE, State Space Models Feb 23, 2026