Add ML Foundations section: Attention and Normalization reviews Two basic-ML building-block review pages with mermaid diagrams and concrete mapping to what Qwen3 / Qwen3.5 and the major VLAs actually use: - ML-Attention.md: full / causal / bidirectional / sliding-window / cross / GQA-MQA-MHA / linear / Gated DeltaNet / QK-Norm. Covers Qwen3 (GQA + QK-Norm), Qwen3.5 (3:1 Gated DeltaNet / Gated Attention hybrid, Feb 2026), Qwen3-VL (Interleaved-MRoPE, DeepStack), plus pi-series prefix-KV, GR00T AlternateVLDiT, DDVLA bidirectional action span, Fast-in-Slow embedded blocks. - ML-Normalization.md: BN / LN / RMSNorm / GN / IN / AdaLN(-Zero) / adaptive RMSNorm / QK-Norm / FiLM, pre vs post-norm. Covers Qwen3 per-head QK-RMSNorm (V not normalized, eps=1e-6), GR00T N1 -> N1.7 vlln + vl_self_attention progression, pi0.7 adaptive-RMSNorm timestep injection, RDT-1B's rejection of AdaLN. - ML.md: hub page linking the two reviews. - Home.md and _Sidebar.md: new ML foundations section wired in.