Track 1
Linear Algebra Core
Vector spaces, maps, spectral methods, decompositions, and geometric intuition.
Advanced learning platform
Linear Algebra and Optimization for Machine Learning
A complete, chapter-driven learning path with clear explanations, worked derivations, and practical intuition for modern ML systems.
24
Chapters
100+
Worked examples
Fast
Concept search
Track 2
Optimization in Practice
Gradients, momentum, adaptive methods, robustness, and convergence behavior.
Track 3
Modern ML Systems
Distribution shift, alignment constraints, scaling dynamics, and system-level tradeoffs.