Raster Notebooks

Interactive guides rendered from source.

• Getting Started — deftm, typed dispatch, value types
• Automatic Differentiation — forward-mode, reverse-mode, value+grad
• ODE Solvers — Lorenz attractor, adaptive solvers, events
• Linear Algebra — Vec/Mat types, LU, Cholesky, SVD
• Optimization — L-BFGS, Nelder-Mead, Newton
• Deep Learning — MLP training with compiled AD
• Agent-Based Modeling — endogenous firm formation
• Geometric Algebra + ODE — rotors, precession