Probability & Bayes

Bayes theorem step by step — prior × likelihood → P(E) → posterior, with medical, spam, and coin presets.

• Foundations
• Vector Math
• Matrix Multiply
• Inverse Matrix
• Eigenvalues & Eigenvectors
• SVD & Orthogonality
• Derivatives

KousKrab — interactive ML simulations in the browser.