Machine Learning with R

  1. Notation

  2. Linear Modeling: A Least Square Approach

  3. Linear Modeling: A Maximum Likelihood Approach

  4. Perceptrons from scratch with R

  5. Neural networks from scratch with R

  6. Neural networks from scratch using matrix with R

  7. Kernel Principal Component Analysis from scratch with R

  8. Eigenvalues and Differential Equations

  9. Singular Value Decomposition

  10. Dynamic Mode Decomposition


  • "First Course in Machine Learning, 2nd ed." by Simon Rogers and Mark Girolami.