EE364 is Stanford's graduate-level course on convex optimization, taught by Stephen Boyd, covering convex sets and functions, duality, and algorithms for solving convex problems. Its lectures are publicly available on YouTube.

Commenters point to it as the next step after linear algebra and linear dynamical systems courses, with lectures freely available on YouTube.

What commenters said (1)

1. Recommendsdvse2011in “Ask HN: How do I start with Machine Learning?”

   Start with the MIT linear algebra course (18.06) by Gilbert Strang and Stanford course on linear dynamical systems (EE263) by Stephen Boyd. Then move on to Boyd's course on convex optimization (EE364). Lectures for all of these are on youtube.

   Do not try to read any books on "machine learning" (most of which are a total mess) before you have this background or you will just end up hopelessly confused.

Related courses

• 18.06 Linear Algebra (Gilbert Strang)MIT OpenCourseWare · 78 recommenders
• EE263 Introduction to Linear Dynamical SystemsStanford University · 4 recommenders
• Stat 110: ProbabilityHarvard University · 18 recommenders
• The Theoretical Minimum (Leonard Susskind)YouTube · 16 recommenders
• 6.042J Mathematics for Computer ScienceMIT OpenCourseWare · 12 recommenders
• Essence of Linear AlgebraYouTube · 10 recommenders
• 6.041 Probabilistic Systems Analysis and Applied ProbabilityMIT OpenCourseWare · 6 recommenders
• Linear AlgebraKhan Academy · 7 recommenders