Mascot image.
#AI#ML#BigData

Artificial Intelligence & Machine Learning

Unofficial notes from two back-to-back courses at REDACTED on Machine Learning, Big Data, and Artificial Intelligence. The content is standard; the difference is the pace and style. Each course runs in a single week (two weeks total), so things move fast.

Format & pace Lectures jump around to quickly deliver the most dense parts, while I am left to fill in the gaps. It is a brutal (but practical) approach. Thus, if these notes feel scattered, that is by design.

What is not covered here (because I am lazy):

  • Formal programming sections/labs (Prolog).
  • Hadoop programming.

Prerequisites

  • Set theory
  • Multivariable calculus
  • Basic algorithms and algorithm analysis

Lean notes. Minimal fluff. Yes, I am lazy.

Notes

Unofficial Notes From Postgraduate Course in ML/AI.

Recommendations

Artificial intelligence: a modern approach

Machine Learning

Mining of Massive Datasets