This is the master page for Notes on Machine Learning posts, in which I summarize in a succinct and straighforward fashion what I learn from Machine Learning course by Mathematical Monk, along with my own thoughts and related resources.

To be added..


  • MM: Mathematical Monk
  • ML: Machine Learning
  • SL: Supervised Learning
  • UL: Unsupervised Learning

  • PSD: Positive Semi-Definite

  • MCTC: Markov Chain Monte Carlo

  • To understand bias-variance “trade-off”, take a quick route:
    (11.5) $\leadsto$ (11.1) (11.2) (11.3) (11.4) $\leadsto$ (11.1) (11.2)

Some other helpful resources: